WHAT YOU’LL DO

Viant is seeking a highly skilled and self-motivated Technical Account Manager to serve as a strategic post-sales thought leader for our most important clients. This role sits at the intersection of technology, measurement, and client strategy, partnering closely with Sales Engineering, Account Management, and product teams to deepen relationships, elevate technical maturity, and accelerate adoption of Viant’s advanced measurement and data solutions. You will play a critical role in scaling strategic accounts post-sale, translating complex technical and measurement capabilities into clear business value, and helping clients fully realize the long-term impact of Viant’s platform.

This role is ideal for someone who thrives as a trusted advisor, enjoys shaping solution strategy, and can influence outcomes across both internal and external stakeholders. The ideal candidate will have a combination of exceptional project management and client service skills, as well as knowledge of the advertising technology landscape. You should have a strong understanding of client service best practices and end-to-end solutions delivery.

THE DAY-TO-DAY

• Serve as a strategic technical thought leader in the post-sale lifecycle, partnering with Account Management to grow adoption, expand use cases, and retain and upsell key accounts.
• Act as a trusted advisor to senior client stakeholders by aligning Viant’s measurement and data solutions to broader business objectives.
• Partner closely with Sales Engineering to ensure continuity of solution strategy from pre-sale handoff through execution and optimization.
• Collaborate with Sales, Business Intelligence, and Operations teams to unblock complex challenges and deliver high-impact solutions for strategic accounts.
• Lead client measurement strategy across Viant Advanced Reporting and third-party measurement solutions to improve insight quality, performance understanding, and ROI.
• Scope and deliver custom reporting solutions that enable advanced analysis, executive-level storytelling, and long-term measurement evolution.
• Develop training materials and documentation to level up internal Sales and Account teams and strengthen post-sale execution.
• Use Google BigQuery SQL to investigate data discrepancies, validate data integrity, and surface actionable insights that inform optimization and decision-making.

GREAT TO HAVE

• 4+ years of experience in Technical Account Management, Account Management, Project Management, Ad Operations, or related roles
• 2+ years experience with Ad Tech platforms such as demand-side platforms (DSPs), data management platforms (DMPs), Customer Data Platform (CDP), and/or clean rooms technology
• Strong understanding of the ad tech ecosystem, including DSPs, ad serving, programmatic buying, onboarding, and measurement
• Ability to clearly articulate complex technical and measurement concepts to both technical and non-technical audiences
• Proficiency in SQL (Google BigQuery preferred) and cloud-based analytics tools
• Strategic mindset with a bias toward action; comfortable operating in ambiguity and influencing without authority

LIFE AT VIANT

Investing in our employee’s professional growth is important to us, but so is investing in their well-being. That’s why Viant was voted one of the best places to work and some of our favorite employee benefits include fully paid health insurance, paid parental leave and unlimited PTO and more. 

#LI-SK1

Noom is on a mission to help people live better, longer. We’re a consumer-led digital health company, connecting people to content, coaching, community, and clinicians, to build lasting habits and live healthier lives. We’re a high-growth organization powered by science, technology, and world-class talent. When you join Noom, on any team, you’ll see the impact of your work on the world.

Our B2B Team

Noom’s B2B team partners with employers, health plans, and organizations to deliver scalable, data-driven health solutions that improve outcomes and drive measurable value. By combining behavioral science with robust analytics, this team ensures our partners have the insights and tools needed to support their populations and make confident, informed decisions.

About the Role

As we continue to grow, we’re seeking a Business Analyst, Commercial to deliver high-quality analytics, reporting, and insights that power client success and commercial decision-making. In this highly cross-functional role, you’ll partner with Client Success, Sales, Product, Data/Analytics Engineering, and Operations to ensure our enterprise clients have accurate, actionable data. Your work will span dashboard development, ad-hoc analysis, and data quality improvements—enabling stakeholders to self-serve insights without compromising accuracy or compliance.

You Will

• Own client-facing reporting and analytics delivery for QBRs, renewals, and expansion efforts, including engagement, outcomes, utilization, and program performance insights
• Deliver high-impact ad-hoc analyses for Sales, Client Success, and leadership, translating ambiguous questions into clear metrics, queries, and actionable outputs
• Build, maintain, and enhance Looker dashboards and explores, improving usability through standardized definitions, intuitive design, and clear documentation
• Ensure data accuracy and consistency by proactively validating dashboards, managing changes in upstream data, and performing regression checks
• Investigate and resolve data discrepancies in partnership with Data/Analytics Engineering, identifying root causes and clearly communicating outcomes to stakeholders
• Support operational analytics across billing, eligibility, and partner reporting requirements, while driving scalability through standardization, automation, and documentation

About You

If you’re interested in shaping the future of health by delivering trusted, scalable analytics that empower enterprise partners, this role may be for you!

You Have

• Bachelor’s degree in Business, Economics, Statistics, Mathematics, Computer Science, or a related field (or equivalent practical experience)
• 3+ years of experience in business or data analytics, ideally in healthcare, benefits, or B2B SaaS environments
• Strong proficiency in SQL, including joins, aggregations, window functions, and debugging complex datasets
• Hands-on experience with Looker or similar BI tools, building dashboards and stakeholder-facing reports
• Proven ability to translate complex, ambiguous questions into clear analyses and actionable insights
• Excellent communication skills, with the ability to explain methodologies and findings to both technical and non-technical audiences
• Experience with healthcare data (e.g., eligibility, enrollment, outcomes, or claims concepts) is a plus
• Familiarity with modern data stacks (e.g., dbt, Snowflake, Databricks, BigQuery) and data quality practices
• Experience supporting Client Success or Sales workflows (e.g., QBRs, renewals, expansion analytics) preferred
• Comfort working in a fast-paced, ticketed environment (e.g., Jira) with shifting priorities

What Makes This Job Amazing

• You’ll help millions of people live healthier lives while supporting enterprise partners at scale
• You’ll work on high-impact analytics that directly influence renewals, expansion, and client trust
• You’ll partner with a strong cross-functional group spanning Client Success, Sales, Product, and Data
• You’ll grow quickly in a transparent, high-performance environment with meaningful ownership

What You'll Earn and Enjoy

• Pay that reflects your impact. Compensation benchmarked to the market and shaped by your impact and value.
• Investment in your future. A 401(k) with company match to help you build long-term financial security.
• Time to truly recharge. Paid holidays, generous time off, Summer Fridays, and a company-wide Summer Break week so the whole team can unplug together.
• Care that covers it all. Access to top-tier medical plans for you and your family, including a premium-free plan option, alongside dental, vision, and life insurance.
• Support for growing families. Paid parental leave to give you the time and flexibility to focus on what matters most.
• And more to help you thrive. Stock awards, a performance-based bonus, and exclusive access to Noom’s products, so you can grow with us, win with us, and enjoy what we build.

The base salary range for this position is $101,000 - $129,000. Actual compensation is determined by job-related factors, including experience, skills, qualifications, and location. 

This role is eligible for our NYC or Princeton office locations, operating on a hybrid schedule (2 days per week on-site).

More About Noom

Noom is a leading whole-person health platform on a mission to help people live better, longer. We combine personalized medication with the science of behavior change and psychology, to help people build lasting habits and live longer, healthier lives. With nationally-recognized, holistic programs spanning weight, diabetes prevention, GLP-1 support, menopause, longevity, and more, we serve millions through health plans, employers, and direct-to-consumer offerings. As a trailblazer in the world of health and wellness, Noom makes healthy living easy, fun, and deeply rewarding.

We’re more than a health tech company—we’re a movement. This belief extends to our culture: we empower our people to think big, act boldly, and take pride in their contributions to shaping the future of health. With a strong remote culture, as well as offices in NYC and Princeton, we’ve been named one of the Best Places to Work by Inc., Fortune, Glassdoor, and Quartz—including honors for technology and diversity.

Join us in shaping the future of health. You’ll be part of a passionate, mission-driven team working to make the world a healthier place—one habit at a time.

Noom is proud to be an Equal Opportunity Employer, and all applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, caste, national origin, physical or mental disability, protected veteran status, age, or any other characteristic protected by applicable law. Noom is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities.

To help protect against potential hiring scams, please be aware that all email communications from the Noom Talent team and/or hiring managers will come only from an @noom.com email address. Please ignore any messaging or communication from other domains (e.g. @noom.team). Noom will never ask you for personal payment, require you to purchase equipment, conduct an interview process or messaging exchange via Microsoft Teams, or extend a job offer without the completion of a multi-step interview process featuring a combination of phone, Zoom, and in-person interviews, as well as references. If you are unsure about the validity of a Noom job posting on another website, we strongly encourage you to apply directly through our website.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About The Role

This is a high-leverage, high-agency role focused on scaling partner-sourced revenue through deep technical alignment with Snowflake, Databricks, GCP, and the broader MarTech & AdTech ecosystem.

You’ll operate more like a GTM strategist and operator than a traditional SE, working across dozens of deals at once through partner influence — not direct sales cycles. You’ll help partners and their customers design the right solutions, accelerate time-to-value, and drive joint adoption, all while maintaining strong technical credibility.

We get excited talking to data engineers, product managers, marketers, and business leaders — and know how to distill technical concepts for different audiences. Your work will make it easier for partners to succeed and, ultimately, grow Hightouch’s partner-sourced revenue.

What You’ll Do

• Drive outbound technical engagement with partner field teams to educate, evangelize, and accelerate joint opportunities
• Act as the technical counterpart for partner AEs and solution architects in enterprise opportunities, supporting discovery, architecture, and solution design
• Build and deliver scalable enablement materials, hands-on labs, demos, and GTM resources for partner teams
• Collaborate with Product, Sales, and Engineering to shape partner strategy and influence product roadmap based on partner and market feedback
• Design and present high-impact, industry- and customer-tailored demos, workshops, and executive briefings
• Serve as a trusted technical advisor to partners building product integrations or joint solutions with Hightouch
• Translate complex customer data challenges into actionable guidance for both technical and executive stakeholders
• Continuously improve knowledge via partner certifications, new tools, and trends in composable CDP, MarTech, AdTech, and data activation
• Travel up to 25% for partner events, enablement sessions, and strategic GTM engagements

What We’re Looking For

• 4+ years in Solutions Engineering, Product, or GTM roles at data infrastructure, MarTech, AdTech, or SaaS companies
• Experience supporting enterprise partners, ideally influencing deals or adoption through technical expertise
• Strong grasp of the modern data stack and composable architectures — familiarity with tools like Fivetran, dbt, Hightouch, Braze, Iterable, or Salesforce Data Cloud is a plus
• Hands-on technical fluency with SQL and cloud data warehouses (Snowflake, Databricks, BigQuery)
• Ability to communicate complex technical concepts to both executive and practitioner audiences
• Proven track record of driving adoption or revenue through partner, field, or cross-functional GTM motions
• Intellectual curiosity, high ambition, strong ownership, and a bias toward action
• Experience working across multiple teams (Product, Engineering, Sales, Support) to solve complex problems
• Comfortable engaging both technical and non-technical stakeholders

Bonus If You Have

• SaaS or cloud architecture experience
• Experience working with channel or ecosystem partners
• Development experience with APIs
• Consulting or startup experience
• Experience bridging Product, Engineering, Support, and Sales teams internally and externally

Compensation

On-Target Earnings Range: $160,000-$230,000 annually
Base Salary Range: $90,000- $161,000 annually
We also offer meaningful equity compensation in the form of ISO options and offer early exercise and a 10-year post-termination exercise window

About this role

We are looking for an experienced Senior Business Intelligence Analyst to scale a critically important function responsible for building and maintaining systems, processes and services that enable us to understand financial performance and unlock key business insights at Faire. The ideal candidate for this role will ensure key accounting procedures are automated in ways that are accurate, efficient, easy-to-understand, and scalable. This role will sit in the Finance department and collaborate with team members from a breadth of functional groups across Faire, including Accounting, Finance & Strategy, Engineering and Data Infrastructure. This role will have a tremendous impact on the ability for Faire employees to use data effectively in order to report numbers externally and make impactful decisions internally. As an early member of a burgeoning team, you will have the opportunity to write the roadmap for how we improve access to business critical data and unlock automation that amplifies the impact of a variety of functions. 

What you’ll do 

• Scope, design, create, and manage complex ETL flows that aggregate and synthesize key business performance metrics and financial reporting, ensuring efficient, accurate, and scalable data models using best practices 
• Act as a trusted analytical partner to the Accounting and Finance teams providing technical expertise, gathering requirements from product and operational teams, and enabling data-driven decision-making and accountability by ensuring core ledgers accurately reflect business changes 
• Collaborate closely with Engineering, Data Infrastructure, and other stakeholders as a key translator and process improver, gathering requirements and delivering impactful data solutions that ensure alignment and efficiency across the organization 
• Lead initiatives to drive data strategy, roadmap planning, and prioritization, ensuring alignment with business objectives 
• Act as a thought leader to expand the team’s influence and impact throughout the Finance team and the broader organization 
• Drive workflow automation and innovation across Finance, including identifying and implementing Gen-AI–enabled productivity solutions to modernize processes and increase team leverage

Qualifications

• 5+ years of work experience in Business Intelligence, Analytics Engineering, Data Analytics, or comparable function 
• Expert in SQL with focus on data modeling, large-scale data processing, and tool development for analytics or Financial use cases. 
• Experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms 
• Experience with analytics workflow tools (examples: Airflow, Docker, dbt), data warehousing and storage (examples: Snowflake, BigQuery, Redshift, S3), and data visualization tools (examples: Mode, Tableau, Looker) 

Nice to have: 

• Experience with Python, R or other programming languages 
• BA/BS degree, ideally in computer science, math or another quantitative field 
• Familiarity with version control using Git and proficiency in command-line tools for workflow automation and data manipulation

Salary Range

San Francisco and New York: The pay range for this role is $174,500 to $240,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment.

This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

What you’ll do

• Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria
• Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans
• Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems
• Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration
• Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations
• Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement
• Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline
• Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production
• Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

What we’re looking for

• 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role
• Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact
• Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans
• Strong foundation in statistics, experimentation, causal reasoning, and measurement
• Experience building tools or products, not just analyses — for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications
• Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work
• Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly
• Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives
• High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications

• Experience in a forward deployed, solutions, consulting, or other client-facing technical role
• Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products
• Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow
• Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery
• Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems
• Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling
• Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like

Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

About the Role

Anthropic manages one of the largest and fastest-growing accelerator fleets in the industry — spanning multiple accelerator families and clouds. The Accelerator Capacity Engineering (ACE) team is responsible for making sure every chip in that fleet is accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.

As an engineer on ACE, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.

You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.

What This Team Owns

The team’s work spans three functional areas. Depending on your background and interests, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

• Data infrastructure — collecting, normalizing, and serving the fleet-wide data that powers everything else. This means building pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalizing billing and usage data across cloud providers, and maintaining the BigQuery layer that the rest of the org queries against. Correctness, completeness, and latency matter here.

• Fleet observability — making the state of the accelerator fleet legible and actionable in real time. This means building cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and driving systemic improvements to scheduling and fragmentation. The work sits at the intersection of Kubernetes operations and cross-team coordination.

• Compute efficiency — measuring and improving how effectively every major workload uses the hardware it’s running on. This means instrumenting utilization metrics across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and collaborating directly with system-owning teams to close efficiency gaps.

• Internal compute tooling — building the platforms and interfaces that make capacity data usable across the org. This includes capacity planning tools, workload attribution systems, cost dashboards, and self-service APIs. The consumers are research engineers, infrastructure teams, finance, and leadership — each with different needs and different levels of technical depth. The work involves product thinking as much as engineering: figuring out what people actually need, defining schema contracts, and making the data discoverable.

You will be placed on a pod based on your background and interests. We are especially focused on hiring for Data Platform, but strong candidates for any of the three active pods will move forward.

What You’ll Do

• Build and operate data pipelines that ingest accelerator occupancy, utilization, and cost data from multiple cloud providers into BigQuery. Own data completeness, latency SLOs, gap detection, and backfill automation.

• Develop and maintain observability infrastructure — Prometheus recording rules, Grafana dashboards, and alerting systems — that surface actionable signals about fleet health, occupancy, and efficiency.

• Instrument and analyze compute efficiency metrics across training, inference, and eval workloads. Build benchmarking infrastructure, establish per-config baselines, and work with system-owning teams to improve utilization.

• Build internal tooling and platforms that enable capacity planning, workload attribution, and cluster debugging. The consumers are other engineering teams, finance, and leadership — not external users.

• Operate Kubernetes-native systems at scale — deploying data collection agents, managing workload labeling infrastructure, and understanding how taints, reservations, and scheduling affect capacity.

• Normalize and reconcile data across heterogeneous sources — including AWS, GCP, and Azure billing exports, vendor-specific telemetry formats, and internal systems with different schemas and billing arrangements.

• Collaborate across organizational boundaries with research engineering, infrastructure, inference, and finance teams. Gather requirements from technical stakeholders, translate them into useful systems, and communicate trade-offs to non-technical audiences.

You May Be a Good Fit If You Have

• 5+ years of software engineering experience with a strong track record building and operating production systems. You write code every day — this is a hands-on engineering role, not a planning or coordination role.

• Kubernetes fluency at operational depth — you’ve operated production K8s at meaningful scale, not just written manifests. Comfort with scheduling, taints, labels, node management, and debugging cluster-level issues.

• Data pipeline engineering experience — designing, building, and owning the full lifecycle of production data pipelines. Experience with data warehouses (BigQuery preferred), schema management, streaming ingestion, SLOs for latency and completeness, and a strong instinct for correctness.

• Observability tooling experience — Prometheus, PromQL, and Grafana are in the critical path for this team. Experience writing recording rules, understanding metric semantics, and building monitoring systems that engineering teams actually rely on.

• Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable.

• Familiarity with at least one major cloud provider (AWS, GCP, or Azure) at the infrastructure level — compute, billing, usage APIs, cost management tooling. Multi-cloud experience is a strong plus.

• High autonomy and strong cross-team communication. You can gather your own requirements, navigate ambiguity, and work across organizational boundaries. Scrappiness and ownership matter more than polish.

Strong Candidates May Also Have

• Multi-cloud data ingestion experience — especially working with AWS and GCP APIs, billing exports, or vendor-specific telemetry formats. Experience normalizing data from external providers with different billing arrangements is directly applicable.

• Accelerator infrastructure familiarity — GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience working with ML training/inference systems at the hardware level.

• Performance engineering and benchmarking experience — building benchmark harnesses, establishing baselines, reasoning about compute efficiency (FLOPs utilization, memory bandwidth, interconnect throughput), and working with system teams to diagnose and improve performance.

• Data-as-product thinking — experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just building pipelines, but thinking about how platform data gets consumed.

• Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or large-scale ML environment. FinOps, chargeback systems, or infrastructure cost modeling.

Familiarity with ClickHouse, Terraform, or Rust. ClickHouse is the team’s current streaming store; Terraform for infrastructure-as-code; Rust for high-performance data collection agents.

YOUR ROLE 

We’re seeking a Business Intelligence Analyst, a role that combines strong technical expertise with strategic thinking and a deep understanding of how data drives business decisions. The ideal candidate is comfortable owning projects end-to-end — from translating business questions into data requirements to delivering polished, executive-ready dashboards and insights. 

You should be highly analytical and detail-oriented, with the ability to manage multiple high-priority initiatives simultaneously.  You must be confident working with complex, multi-source datasets and capable of identifying discrepancies, troubleshooting issues, and ensuring data integrity. Just as important, you should be able to communicate findings clearly to non-technical stakeholders, translating data into actionable recommendations. 

In a media and marketing analytics environment, we’re looking for someone who understands campaign performance metrics, audience measurement, and cross-channel reporting. You should have experience building client-facing dashboards and be comfortable operating in fast-paced, deadline-driven settings where accuracy and presentation quality are critical. 

 REQUIREMENTS 

• 2+ years of experience in Business Intelligence, Data Analytics, or Marketing/Media Analytics
• Highly proficient with Tableau (dashboard development, calculated fields, LOD expressions, performance optimization)
• Strong SQL skills, including writing complex queries and joining multiple data sources
• Experience working with marketing/media data  
• Proven experience building executive- or client-facing dashboards
• Experience migrating or rebuilding reporting environments (e.g., Datorama to Tableau) preferred
• Strong understanding of KPI development and performance measurement frameworks
• Ability to manage multiple projects simultaneously and meet tight deadlines
• Excellent communication skills with the ability to translate technical findings into business insights 

PREFERRED QUALIFICATIONS (NICE-TO-HAVE) 

• Experience migrating reporting platforms (e.g., Datorama → Tableau)
• Experience embedding dashboards into web platforms or proprietary systems
• Familiarity with data warehousing tools (Snowflake, BigQuery, Redshift)
• Experience working in an advertising agency or client-service environment
• Exposure to ETL tools or API-based data integrations
• Experience supporting new business pitches or building “demo-ready” dashboards
• Experience mentoring junior analysts or reviewing others’ work
• Experience building and managing standardized dashboard templates 

This role requires a hybrid schedule and will be based in our New York, NY office (Tuesday through Thursday) and work fully remotely on Mondays and Fridays each week.

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We're looking for a sharp, analytically rigorous Senior BI Analyst to join our growing Business Intelligence team. This is a hands-on, high-impact role at the center of how we understand and grow our business. You'll play a key role in the foundation of our data visualization ecosystem, build performance dashboards that drive decisions, conduct complex analyses to inform revenue-driving workstreams, and translate data into stories that non-technical stakeholders can act on. The right candidate is deeply comfortable with complicated datasets and cross-functional communication.

What You’ll Do:

• Architect and write the semantic layer for our new data visualization platform as we migrate from our current tooling.
• Build, iterate, and maintain dashboards and reports that give business stakeholders clear visibility into performance across the funnel.
• Own weekly full-funnel performance reporting, surfacing trends, anomalies, and opportunities with clear business context.
• Conduct ad hoc, multi-step analyses using advanced statistical methods, complex SQL queries, and Python scripts to answer granular business questions.
• Understand and improve existing data pipelines in partnership with Data Engineers, understanding data flows end-to-end.
• Present findings to business stakeholders, translating highly technical analysis into clear, actionable insights.
• Proactively identify areas for measurement improvement, optimization opportunities, and testing.
• Leverage AI tools to accelerate work, using your own judgment and expertise to critically evaluate and improve AI outputs

What We’re Looking For:

• 3+ years of experience in a highly quantitative and analytical environment.
• Comfort in a fast-paced and often changing environment, with an inclination to solve new problems and learn new skills
• Bachelor's or Master’s degree in Data Science, Statistics, Mathematics, or a related quantitative field preferred. 
• Strong SQL and Excel
• Python (Pandas, Nmpy, Statsmodels)
• Experience in or exposure to BI/data visualization tools (Tableau, Looker, or similar)
• Familiarity with data warehouse environments (Snowflake, BigQuery, Redshift)
• Understanding of data pipelines and semantic layer concepts

Compensation: 

This range reflects total cash compensation, which may include base salary only or base salary plus target bonus, depending on the role. Where eligible, equity may also be offered separately and not included below. Actual compensation varies based on location, experience, and qualifications.

• Total Cash Compensation Range: $100,000 - $140,000 per year

*New York City Total Cash Compensation Range: $125,000- $170,000 per year

Additionally, the following benefits are provided by Red Ventures, subject to eligibility requirements.

• Health Insurance Coverage (medical, dental, and vision)
• Life Insurance
• Short and Long-Term Disability Insurance
• Flexible Spending Accounts
• Holiday Pay
• 401(k) with match
• Employee Assistance Program
• Paid Parental Bonding Benefit Program
• Flexible Paid Time Off (PTO): We believe time to rest and recharge is essential.  That’s why we offer a generous and flexible PTO policy.  Full-time employees accrue 20 days of PTO for a full calendar year annually, with an increase to 25 days after five years of service.

Who We Are:

Red Ventures is a global portfolio of high-growth companies — spanning several U.S. businesses, a joint venture in the health services industry, and strategic investments in Europe. Their businesses include The Points Guy, Lonely Planet, Bankrate, the Allconnect Platform, RV Home Client Growth, RV Growth & Transformation, Sage Home Loans Corporation, and more. Across the portfolio, Red Ventures businesses deliver seamless digital experiences for consumers, help Fortune 100 clients solve large-scale digital growth challenges, and create world-class experiences and opportunities for employees. Learn more at redventures.com and follow @RedVentures on LinkedIn and Instagram.

At Red Ventures, we believe diverse, inclusive teams are better. To help you better understand our core values and beliefs, we encourage you to watch this brief YouTube video: Our Belief Statements. This will give you insight into the principles that guide our work and our commitment to fostering an inclusive environment.

Red Ventures is an equal opportunity employer that does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or any other basis protected by law. Employment at Red Ventures is based solely on a person's merit and qualifications. 

We are committed to providing equal employment opportunities to qualified individuals with disabilities. This includes providing reasonable accommodation where appropriate. Should you require a reasonable accommodation to apply or participate in the job application or interview process, please contact accommodation@redventures.com. 

If you are based in California, we encourage you to read this important information for California residents linked here.

At Red Ventures, we believe in real human connection. That’s why we do not hire someone through text, social media, or email only. As part of the hiring process, you should expect live conversations with RV teammates before any offer is made. Also, keep an eye on the sender: we only use official @redventures.com email addresses at the portfolio level or business specific email addresses (e.g., @thepointsguy.com), not ones like “redventurescareer.com.” We will never ask candidates to send money, buy equipment, or share financial account info during your journey with us. You can always find our open roles on redventures.com— if you receive a message that seems suspicious, please use redventures.com to verify the opportunity.

For more, the U.S. Federal Trade Commission has published helpful articles to help individuals learn more about protecting themselves from recruiter scams. If you think you’ve been targeted, feel free to report it to your local authorities. Stay safe out there!

#li-dh1

#BR

About the Role

We are seeking analytical talent to turn passion for data and support of world-class journalism into decision-making insights. As part of the Data and Insights Group (DIG), you will join a large community of accomplished analysts who partner with Product, Engineering, and Design teams across the business. You will be embedded within our platforms teams and report to the Director, Data & Insights.

Responsibilities:

• You will write SQL, Python, DBT code to pipeline and analyze big datasets across multiple domains
• You will develop data models, pipelines, infrastructure, and metrics that create evergreen solutions and support the wider analytics team
• You will design and run A/B tests to quantify the effectiveness & business impact of platform enhancements
• You will perform strategic analysis to advise and influence our platform roadmaps
• You will build data visualizations and dashboards to expand self-service access to our insights
• You will develop insights on our push channel, helping to optimize platform capabilities that drive engagements & revenue
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• Advanced proficiency in SQL and experience working with cloud based relational databases (such as BigQuery)
• 3+ years of experience working in product analytics, data science or other data teams
• 3+ years of experience with data visualization tools such as Hex, LookML, PowerBI
• 3+ years of experience in at least one additional scripting language like Python, R, or JavaScript (Python preferred)

Preferred Qualifications:

• 1+ years of experience with version control (Github, code review)
• 1+ years of experience with experimentation and other statistical inference methods
• 1+ years of experience working in dbt
• 1+ years of experience working with a data notebook tools like Jupyter Notebooks
• Familiarity with email & push campaigns + product channel analytics.

REQ-019350

About the Role, Mission or Department Overview

The New York Times is looking for an analyst who is can dive into our advertising analytics and optimization challenges in our digital advertising business.

As a Business Data Analyst, you will serve the Advertising and Sales teams by analyzing our products and their supporting data sources, using insights to help innovate and improve our sales efforts. You will partner with Ad Product, Sales, Revenue Operations, Sales Operations, and Finance to provide sales performance and trend insights. You will report into our Manager, Business Analytics.

Responsibilities:

• You will analyze advertising and sales datasets to optimize overall performance. Develop, monitor, and analyze performance through dashboards and provide strategic optimization alerts and recommendations.
• You will provide important business insights and actionable analysis to Sales, Advertising, and Product leadership based on performance trends
• You will manage daily ad performance and sales requests from Ad Product, Sales, and Finance teams, providing product recommendations, inventory trends, or alternative options.
• You will engage with data engineering and other analytics teams to develop new data pipelines and datasets and ensure data governance.
• You will translate high-level business questions into insights to lead rapid decision-making.
• You will help establish requirements for analytics tools and reporting dashboards.
• You will investigate and reconcile data discrepancies between different ad-servers, internal databases, and financial reporting systems.
• You will develop quantitative analysis and statistical models to support advertising decisions.
• You will monitor NYT properties to ensure ads are delivering as expected
• You will demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• Advanced SQL proficiency
• Advanced Excel Proficiency (Pivot Tables, XLOOKUP, Complex Formulas)
• 2+ years experience in a quantitative field or equivalent educational experience
• 1+ years of experience working with both business and technical (IT) teams

Preferred Qualifications:

• 1+ years of experience with Data Visualization tools (Tableau, PowerBI, Mode, or Looker)
• Knowledge of Python for statistical analysis
• 1+ years of experience in digital advertising
• 1+ years of experience using BigQuery and Google Ad Manager
• BA/BS in Economics, Statistics, Mathematics, or related field

REQ-020003

The Election Analytics team produces flagship, standard-setting elections coverage, including the live, election night statistical model known as the Needle and The New York Times/Siena Poll. Both of those efforts rely on one of the most comprehensive election data operations in media, with the voter file at the core.

We’re just scratching the surface of all the journalistic products we could produce with the voter file and the rest of the data we collect — absentee files, precinct-level results, live turnout figures, poll results and more. But our tooling has not always kept pace with our ambitions.

You will be responsible for owning this mass of data end-to-end, for ensuring that we have reliable, automated pipelines for putting the data into consistent formats and for validating that the data is being transformed correctly. You will also be responsible for the tooling to work with the data, ensuring that more data journalists can leverage it without the existing steep learning curve. (We are an R shop, though prior R experience is not a necessity.) If you like solving problems for which there is little, if any, documented precedent, this would be a fun job for you.

Your work will ensure that we can even more regularly tell compelling stories about voting patterns and elections, whether they take the form of articles or evolve into new products that deliver as much insight as our polls and the Needle. You will be a key part of producing these stories and products, working with other journalists to understand the data that is available and transforming the data into new formats as needed.

You will also contribute to other areas of our elections coverage based on your skills and interest, including opportunities to pursue original reporting on your own and to collaborate on stories, graphics and tools for readers based on government, polling and other types of data.

This is an in-office position based in New York City or Washington, D.C., and includes regular attendance in the office four days each week. There may be some flexibility to work remotely per your departmental guidance.

To apply, you MUST include a cover letter of no more than 300 word that...

        - described the solution you developed to a unique technical problem, preferably one around data; and

        - directly addresses your interest in and experience with the type of data you expect to be working with in this role

Responsibilities:

• Develop libraries in R that form the basis of our apps

• Work with colleagues to onboard them to existing tools and develop new tooling as needed

• Maintain the pipelines that process and score the voter file, a list of registered voters that forms the basis of much of our work

• Develop tooling to support, deploy and monitor R apps in Google Cloud and Amazon Web Services

• Balance engineering principles with the need to move at the speed of news

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

• This role reports to the Director of Election Analytics

Basic qualifications:

• 5+ years of relevant work experience

• Familiarity working with large data sets and with best practices in data management

• Experience working with data-oriented programming languages, such as R or Python, specifically creating packages or libraries, debugging third-party software and otherwise using scripting languages to power complex apps

• Experience working with cloud computing providers such as Google Cloud Platform or Amazon Web Services

• Experience solving complex problems that require developing original solutions

• Experience working on tight deadlines and making tradeoff decisions to ensure the deadlines are met

• Experience working collaboratively with people of different skills and backgrounds

• Willingness to work a flexible schedule as needed to support coverage of elections and polls

Preferred qualifications: 

• Journalistic experience or interest in reporting, particularly on elections

• Experience developing ETL pipelines, working with orchestration tooling, and ensuring reliability and observability

• Experience with Google BigQuery or other OLAP databases; knowledge of patterns for data warehousing and analytical stores; or knowledge of formats and tools for working locally with large data sets

• Experience developing high-speed modeling applications

• Experience building productionized apps, preferably HTTP-based

This position is represented by the NewsGuild of NY.

REQ-019971

About the Role

We are seeking analytical talent to turn passion for data and support of world-class journalism into decision-making insights. As part of the Data and Insights Group (DIG), you will join a large community of accomplished analysts who partner with Product, Engineering, and Design teams across the business. You will be embedded within our platforms teams and report to the Director, Data & Insights.

Responsibilities:

• You will write SQL, Python, DBT code to pipeline and analyze big datasets across multiple domains
• You will develop data models, pipelines, infrastructure, and metrics that create evergreen solutions and support the wider analytics team
• You will design and run A/B tests to quantify the effectiveness & business impact of platform enhancements
• You will perform strategic analysis to advise and influence our platform roadmaps
• You will build data visualizations and dashboards to expand self-service access to our insights
• You will develop insights on our push channel, helping to optimize platform capabilities that drive engagements & revenue
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• Advanced proficiency in SQL and experience working with cloud based relational databases (such as BigQuery)
• 3+ years of experience working in product analytics, data science or other data teams
• 3+ years of experience with data visualization tools such as Hex, LookML, PowerBI
• 3+ years of experience in at least one additional scripting language like Python, R, or JavaScript (Python preferred)

Preferred Qualifications:

• 1+ years of experience with version control (Github, code review)
• 1+ years of experience with experimentation and other statistical inference methods
• 1+ years of experience working in dbt
• 1+ years of experience working with a data notebook tools like Jupyter Notebooks
• Familiarity with email & push campaigns + product channel analytics.

REQ-019389

About the Role, Mission or Department Overview

As a Software Engineer on the Experimentation & Instrumentation team, you will build and maintain interfaces and golden paths that make it easy for product teams to instrument experiments and behavioral events and connect experiment outcomes to downstream user behavior and engagement metrics. You will work with Product, Data, and other engineering teams to deliver SDKs and interfaces that connect our products and systems to the data platform, powering data-informed decisions at scale.

This is a hybrid role reporting to the Senior Engineering Manager within the Data Platforms mission.

Responsibilities:

• Build services, SDKs, and interfaces that power experimentation and behavioral event instrumentation across our products.

• Partner with Product, Analytics, and other engineering teams to deliver roadmap work that improves how we run experiments and instrument user behavior data.

• Support the full experimentation and instrumentation stack, from event collection to data modeling and downstream usage, including changes to schemas and contracts.

• Build for reliability and observability, including monitoring, alerting, runbooks, and participation in incident response for the systems you own.

• Create clear documentation, examples, and integration guide that help engineers and partners use our tools.

• Contribute to code and design reviews and pair programming to improve code quality and maintainability across the team.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 3+ years of professional software engineering experience building backend or full‑stack services, data pipelines, or client-side SDKs.

• Proficiency in at least one modern programming language (for example, Java, Go, Python, or JavaScript/TypeScript).

• Experience with standard engineering practices, including automated testing, code review, CI/CD, and operating production systems.

• Familiarity with Agile software development practices.

• Break down complex problems and deploy incremental, high-quality solutions.

• Experience communicating blockers, updates and resolutions to customers and other partners.

Preferred Qualifications:

• Experience working with data‑intensive or event‑driven applications, such as logging, analytics, or experimentation systems.

• Experience operating in a dual-cloud environment (GCP/AWS), including running production services in one or both clouds.

• Experience designing or maintaining SDKs or shared libraries used by other engineering teams.

• Experience designing and evolving data schemas or event contracts in collaboration with analysts and product partners.

• Experience with a data warehouse like BigQuery, Snowflake or Redshift.

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-019838

About the Role

We are seeking a Principal Software Engineer to lead the architecture and evolution of our data and machine learning infrastructure. This role will shape the foundation on which data-driven products, analytics, and AI applications are built. You will design systems that enable large-scale data processing, reliable pipelines, and efficient machine learning development—from feature engineering to real-time model serving.

As a principal engineer, you will partner with product, data science, and platform teams to set technical direction, drive adoption of reusable frameworks, and mentor engineers across the organization. You will ensure that both data and ML platforms are scalable, reliable, cost-efficient, and compliant with privacy and governance standards.

The core of the Data Platform is a data lake on AWS S3 with Apache Iceberg as the table format to ensure reliability. Data ingestion is standardized through Confluent Kafka for real-time streaming and Fivetran for ingestion of files and change-data. The transformation layer is decoupled from storage, using Apache Flink for stream processing, AWS Glue (Spark) for core ETL , and dbt/Athena for building analytical data models. The platform serves data through fit-for-purpose data stores, including Amazon DynamoDB for low-latency applications and Google BigQuery as the primary engine for analytics and BI.

You will report to the Sr. Director of Engineering. This role can be remote in the US, with a preference for candidates in the New York City area.

Responsibilities:

• Architect & Build Platform: Design and evolve infrastructure for data ingestion, storage, batch and streaming pipelines, and machine learning workflows

• Enable ML at Scale: Build systems for training, deploying, monitoring, and governing models, including feature stores, registries, and inference platforms

• Reliability & Observability: Ensure end-to-end system reliability, monitoring, and cost transparency across data and ML workloads

• Self-Service Platforms: Deliver frameworks and APIs that enable engineers, analysts, and ML scientists to build and operate solutions independently

• Innovation & Standards: Evaluate and introduce emerging technologies (vector databases, distributed training, orchestration frameworks, LLM stacks) and establish adoption guidelines

• Cross-Functional Leadership: Partner with platform, product, and engineering and ML science leaders to align on strategy and accelerate delivery

• Mentorship & Influence: Guide senior and staff engineers, lead architecture reviews, and raise the technical bar across data and ML domains

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world
  
  

Basic Qualifications:

• 10+ years of software engineering experience with a focus on distributed systems, data platforms, and ML infrastructure or equivalent

• Proven ability to influence technical direction across multiple teams and mentor senior/staff engineers

• Proven expertise in data processing frameworks and table formats (e.g. Spark, Flink, Iceberg) and orchestration tools (e.g. Airflow, Kubeflow)

• Deep knowledge of ML infrastructure: model training pipelines, feature stores, registries, serving, and monitoring

• Strong programming skills in Python and at least one compiled language like Java or Go

• Experience designing systems with scalability, reliability, and cost-efficiency as first-class concerns

• Cloud platform experience (AWS, GCP), familiarity with Kubernetes and modern data platform architectures

• Familiarity with compliance and governance in data/ML systems (auditability, privacy, explainability)

• Familiarity with the data lakehouse paradigm and medallion architecture

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Remote

REQ-018968

The New York Times is an industry leader in visual and interactive journalism, excelling in data visualization and innovative approaches to covering the news.

We are looking for an audience editor with strong analytical skills to join the newsroom Audience team and partner with The Upshot, Graphics and Weather desks. This role sits at the intersection of audience strategy, newsroom analytics and editorial collaboration, helping these desks reach more readers while deepening our understanding of how audiences engage with data-driven journalism.

Some of our most far-reaching and engaging journalism comes from our graphics and data teams. We are looking for someone who can both analyze audience behavior and translate those insights into editorial and distribution strategies that expand the reach and impact of this work.

This editor will combine audience strategy with hands-on data analysis. They will interpret and translate how readers discover, engage with and share visual journalism; surface insights that inform coverage and presentation; and help ensure that stories reach the widest possible audience across Times platforms and beyond.

They will work closely with editors and our newsroom audience analytics team to inform both day-to-day coverage and long-term editorial projects, including interactive data features like election results, poll tracking and weather maps.

They will develop analyses and dashboards that help the desks understand how their work performs and then make strategic recommendations based on that audience research.

This is an in-office position, based in New York City and includes regular attendance in the office four days each week. There may be some flexibility to work remotely per your departmental guidance.

Responsibilities

• Partner with the newsroom audience analytics team to build on their ongoing analyses and deep dives on data-driven and visual coverage

• Interpret data and signals to shape how we present interactives and data-driven journalism both on- and off-platform

• Write SQL to analyze large datasets and support data-oriented analyses to be presented to senior desk leadership

• Optimize stories for search; identify trending topics and competitor trends that the desks should know about or take action on

• Contribute to regular audience performance updates including but not limited to morning audience notes, monthly masthead presentations and quarterly and annual audience reports to company leadership

• Work with editors and journalists on best social media practices, including framing coverage for specific audiences, and leveling up journalists' awareness of platform opportunities beyond social media

• Build community by monitoring comments for trends and facilitating conversations between readers and Times reporters and editors on our interactive and visual journalism

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

• This role reports to the Senior Audience Editor, News

Basic Qualifications

• 3+ years of experience in digital journalism, audience development, newsroom analytics or a related field

• Strong analytical skills and experience working with audience data to inform editorial or strategic decisions

• Proficiency in SQL and experience working with relational databases

• Experience collaborating with analytics or data science teams to conduct analysis and translate insights into strategy

• 1+ years of experience working with data analytics or data science teams to deliver analysis and make data-informed strategic decisions

• Strong writing and editing skills, and knowledge of Times style or the ability to absorb and apply it quickly

Preferred Qualifications:

• 1+ years of experience in at least one additional scripting language like R, Python, or JavaScript (R preferred)

• 1+ years of experience with version control (Git or other version control workflows)

• Experience working in big data environments such as Google BigQuery or AWS

• Experience with data visualization and analytical tools such as ggplot and tidyverse

• Familiarity with media industry analytics, audience trends or platform strategy, as well as interest in data visualization in news coverage

• Experience analyzing search, referral and social traffic patterns

• Experience with mainstream and some emerging social channels, with a willingness to learn about new platforms

• A dedication to The Times and its journalistic mission

• A strategic and analytical mindset, with comfort working with data and testing and iterating to find what resonates with various audiences

REQ- 019985

About the Role:

The Cloud Cost & Capacity Engineering (CCCE) team bridges finance, engineering, data, and product to turn cloud usage and spend into strategic insight and predictable investment decisions. We enable teams across The New York Times to make smart, data-informed choices about how they use the cloud, balancing cost, capacity, and risk across AWS and GCP.

As a Senior Capacity Engineer, you are the primary technical authority for how we model, plan, and optimize cloud capacity. You will own end-to-end capacity strategy for key platforms and critical user journeys (CUJs), defining how we balance headroom, efficiency, and resilience. You'll partner closely with engineering, SRE, and Finance to make sure we can handle peak moments without surprise spend or over-provisioning.

This role is ideal for someone who enjoys working at the intersection of capacity engineering, architecture, and cloud economics, and who is comfortable influencing senior stakeholders without direct people management responsibility.

You will sit at the center of how The New York Times manages cloud capacity and growth. Your work will directly impact our ability to support major news events, launch new products confidently, and keep cloud growth within targets—while giving teams the flexibility and clarity they need to build great experiences for our readers.

Responsibilities:

Capacity & Forecasting

• Build and maintain forward-looking capacity models for major platforms, environments, and CUJs using historical trends, product roadmaps, and traffic patterns.
• Translate growth (traffic, data, features, video) into infrastructure capacity plans that balance performance, resiliency, and cost.
• Quantify “cost of capacity vs. risk” trade-offs and provide clear recommendations for both run-rate and new initiatives.
• Partner with CCCE and Finance to improve cloud forecast accuracy and connect capacity assumptions to budgets, multi-year plans, and cloud commitments.

Architectural Optimization

• Partner with Cloud Engineering and platform teams to analyze scaling behavior, rightsize resources, and implement cost-efficient patterns (autoscaling, reservations/savings plans, storage policies, non-prod guardrails).
• Identify systemic capacity and efficiency risks across architectures and drive solutions via guardrails, reference designs, and lifecycle automation.
• Embed capacity and cost considerations into design reviews and intake for new services and cost-impacting changes.

Tooling, Signals & Reporting

• Leverage and evolve cost and capacity tooling (e.g., FinOut, billing exports, dashboards) to produce actionable capacity signals rather than raw data.
• Work with SRE and observability teams to align capacity signals (utilization, saturation, headroom thresholds) with reliability and performance goals.
• Create concise views, narratives, and recommendations that help mission leads, engineering managers, and finance partners understand capacity posture and trade-offs.

Partnership, Influence & Enablement

• Act as a technical partner to engineering teams, helping them design and operate services that are elastic, efficient, and predictable.
• Mentor engineers and analysts on capacity planning best practices, modeling techniques, and how to interpret capacity signals.
• Represent CCCE in cross-functional forums where cloud growth, reliability, and investment trade-offs are discussed.
• Contribute to training, documentation, and office hours that make capacity planning a shared, repeatable practice across engineering.
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.
• This role reports to the Director of Engineering, Developer Platforms.

Basic Qualifications:

• 8–10+ years in capacity engineering, cloud cost management, SRE, or platform/infrastructure engineering in a public cloud environment, partnering closely with engineering and finance on infrastructure investment and cost predictability.
• Experience modeling capacity and cloud spend for large-scale, distributed systems, including forecasting, scenario planning, and cost-to-serve analysis.
• Strong understanding of cloud deployment architectures (compute, storage, networking, data) and the cost and capacity drivers behind them.
• Proficiency with cloud cost and usage tools (e.g., FinOut, Cloudability, AWS Cost Explorer, GCP Billing/Export) and observability platforms to derive capacity signals.
• Advanced data analysis and modeling skills (e.g., Google Sheets, SQL/BigQuery) to build, validate, and communicate capacity models and forecasts—even with imperfect data.

Preferred Qualifications:

• Background in FinOps or cloud financial management, especially in high-traffic or subscription environments, and familiarity with readiness and reliability practices (e.g., load testing, capacity readiness reviews, Always Ready–style programs).

REQ-019976

About the Role, Mission or Department Overview

The New York Times is looking for a Senior Analyst to join our Enterprise Analytics Team within the Data and Insights Group (DIG).

As part of the Enterprise Analytics team, you will work with teams across DIG, Data Platforms, and Strategy. You will uncover meaningful patterns from our data, automate reporting, create consistent metric definitions, in support of a trustworthy, scalable enterprise data foundation. You will help shape an enterprise-wide view of the journalistic, product and commercial drivers of the business to inform strategy, quarterly earnings and other related deliverables. You will report to the Director, Enterprise Analytics.

Responsibilities:

• You will collaborate with Strategy teams and DIG counterparts to deliver holistic analyses and performance reporting (slide decks, memos) on audience, engagement, and subscription growth to executives, the Board, and Wall Street

• You will build and maintain centralized reporting dashboards and automated reports on enterprise metrics, for use by analysts and business stakeholders across the organization

• You will code in R or Python to analyze data, build visualizations, and create automated reporting infrastructure

• You will write SQL to build pipelines, reporting architecture, and analyze large datasets.

• You will demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of experience working with data analytics or data science teams to deliver reporting and analysis

• Proficiency in SQL and experience working with relational databases

• 2+ years of experience in at least one additional scripting language like R or Python

• 1+ years experience with data visualization and presenting insights from data

Preferred Qualifications:

• 1+ years of experience working in big data environments such as BigQuery or dbt, querying 10M+ rows

• 1+ years of experience working in dbt or other data transformation or scheduling tool

• 1+ years of experience with version control (Github, code review)

• 1+ years of experience with subscription or revenue metrics

REQ-019896 

About the Role:

We are part of a New York-based technology organization with a remote-friendly workplace that includes engineers around the world. We value transparency and openness, learning, community, and continuous improvement. Check out the Times Open blog, which is written by engineers and other technical team members, and follow @nytdevs on Twitter to see what we're up to.

Responsibilities:

• Design, model, and implement complex ELT/ETL pipelines for the cleansed and curated data layers in the medallion architecture, taking full ownership of the data product's structure, partitioning, documentation, and performance characteristics.

• Develop advanced data transformations using dbt (data build tool) for relational data modeling and PySpark for large-scale data processing within the Lakehouse, ensuring outputs meet strict Service Level Agreements and quality standards.

• Collaborate across teams to define requirements and translate them into robust and scalable data models suitable for analytic consumption.

• Manage the physical data storage across both GCP and AWS, selecting optimal file formats and designing efficient partitioning and clustering strategies.

• Administer and tune Spark compute resources (e.g., Dataproc, EMR, or managed services) to optimize job execution time and cost.

• Own core components of our centralized analytics environment, specifically focused on Hex, integrations, and the methods of data exposure and access controls; and support data activation strategies, ensuring seamless data consumption by analytic tools.

• Optimize user queries and access patterns to maintain platform performance and cost efficiency.

• Implement centralized data quality checks and observability mechanisms within the data pipeline to proactively identify and resolve data issues.

• Contribute to the implementation of metadata management, data lineage, and role-based access control (RBAC) initiatives across the Lakehouse environment.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of hands-on experience in a Data Engineering, Data Warehousing, Analytics Engineering or equivalent role

• Proficiency in SQL and experience with complex, production-level data modeling (dimensional modeling, Kimball, OBT, or Data Vault)

• Demonstrated experience designing, developing, and deploying end-to-end data products through the full Software Development Lifecycle

• Experience with a Cloud Data Warehouse, like BigQuery

• Proficiency in Python for scripting and data manipulation, including knowledge of PySpark or other Spark APIs

• Familiarity with cloud services and data storage components in at least one major cloud provider (GCP or AWS)

• Experience with workflow orchestration tools (e.g., Airflow, Cloud Composer, or Prefect) and version control systems (Git)

Preferred Qualifications:

• Experience operating in a dual-cloud environment (GCP/AWS)

• Experience with Infrastructure-as-Code (IaC) tools like Terraform

• Experience with advanced Lakehouse file formats like Iceberg or Delta Lake

• Familiarity with experimentation or A/B testing platforms and the data required to support them

• Experience in data product quality standards through integration advanced testing, quality checks, and monitoring into the CI/CD pipeline

REQ-019489

#LI-hybrid

About the Role

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning Platform (MLP) team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models with low-latency and Service Level Agreements (SLAs) guaranteed by the MLP.

We are looking for a Software Engineer, with a focus on MLOps, to join our Machine Learning Platform team to help solve creative challenges around Machine Learning infrastructure for the New York Times.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform at scale

• You will build infrastructure to train and test algorithms that provide real-time content recommendations and personalization

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will promote developer productivity by rolling out capabilities that maximize self-sufficiency and minimize the toil in learning those capabilities in building scalable applications with high speed, quality, and performance

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD

• Familiarity with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, Drone, Triton, TensorFlow, scikit-learn, DataDog

• Experience building real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with stakeholders to understand pain points, observe patterns, and identify opportunities for improvements

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019501

#LI-Hybrid

About the Role

The New York Times is looking for a Senior Software Engineer, with a focus on ML platform development, to join our Machine Learning & AI team to help solve creative challenges around Machine Learning infrastructure.

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements (SLAs) guaranteed by our platform.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform that supports large-scale multi-tenant workloads

• You will build a platform to train and test algorithms that provide real-time content recommendations and personalization to our readers

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will build a platform that supports the full Machine Learning workflow; from model training, testing and production deployment at high scale and low latency

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 5+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD (Drone, Argo, Jenkins, etc)

• Experience leading the development of large-scale, data-driven, distributed multi-tenant systems

• Proficiency with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, BigTable or other NoSQL datastores such as Cassandra, DynamoDB, Redis

• Familiarity with ML tooling such as Triton, TensorFlow, scikit-learn

• Experience building the infrastructure that power real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with partners to understand pain points, observe patterns, and identify opportunities for improvements

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019502

#LI-hybrid

About the Role:

The New York Times is seeking an Engineering Manager to lead our Audience Targeting team. This team builds high-throughput systems—including APIs, databases, and pipelines—that power personalized communication for millions of readers across email, push, and other channels.

Leading a team of 6–9 engineers, you will drive a strategy of personalization: sending the right message to the right subscriber or potential subscriber at the right time, often at the high-stakes speed of breaking news. You will empower your team to develop the technical vision for our targeting platform, partnering with product and data leaders to build a scalable, intelligent ecosystem that ensures our messaging has maximum impact.

Responsibilities:

• Lead and Develop the Team: Manage a team of 6–9 backend engineers, fostering their career growth through coaching, mentorship, and continuous feedback. Promote a culture of collaboration, engineering excellence, and psychological safety.
• Drive Technical Strategy: Guide the team in designing, building, and maintaining high-throughput, low-latency services and pipelines for audience targeting. Drive decisions on architecture and technology selection within our AWS-forward ecosystem.
• Execute and Deliver: Collaborate across functions and stakeholders to define roadmaps, plan sprints, and deliver impactful projects. Ensure the team's work is aligned with broader company objectives.
• Ensure Operational Excellence: Own the reliability, scalability, and performance of the team's services. Champion robust monitoring, alerting, and on-call practices to maintain high availability for our critical systems.
• Collaborate Across Boundaries: Build strong relationships and coordinate projects across other teams and organizations to ensure successful outcomes. Represent the team in technical discussions and clearly articulate technical challenges and risks.
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.
• You will report to the Director of Engineering for Messaging Platforms.

Basic Qualifications:

• 2+ years of experience in an engineering management or people leadership role
• 5+ years of hands-on experience as a software engineer
• Demonstrated technical leadership in the delivery of enterprise-scale software projects
• Experience hiring, developing, and retaining software engineers
• Familiarity with cloud-based infrastructure (AWS preferred)

Preferred Qualifications:

• Leadership & Delegation: Proven success in developing emerging talent and delegating complex projects to empower engineers to grow into technical owners
• Technical Expertise: Experience with Golang, AWS (specifically Lambda, SQS, and DynamoDB), event-driven architectures, and distributed systems at scale
• Data Expertise: Experience working with large-scale data storage and analysis tools such as Postgres and BigQuery
• Collaboration: Experience working on projects with non-engineering partners (e.g., Data Science, Marketing, Legal, Privacy)

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-020044

About the Role, Mission or Department Overview

As part of the Data and Insights Group (DIG), you will join a large community of accomplished data analysts who partner with Product, Engineering, Design, and PMO teams across the business. You will help inform the data and insights strategy for the Subscriber Revenue team as an individual contributor. This team leads innovation in new revenue-generating models for the company, including initiatives like the exploration and launch of our family plan. You will have a direct and quantifiable impact in our subscribers business. You will report to the Executive Director, Growth Analytics.

Responsibilities:

• You will define strategy within your team's problem space and oversee the definition and execution of solutions
• You will present data-oriented analyses to high-level partners to guide team strategy
• You will develop best practices for experiment design, including advising on hypothesis generation, sample size, and counter metrics
• You will deliver test analysis, advice on future tests and next steps
• You will collaborate with product, data science, and tech to bring to life new targeting and insight tools
• You will lead all phases of analytic work: from problem definition to representation of results
• You will produce insights, advocating for them and driving them into action
• You will demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 5+ years of experience working with data analytics or data science teams to deliver analysis or a quantitative degree
• Mastery of Proficiency in SQL and experience working with relational databases
• 1+ years of experience with data visualization tools such as Mode, Tableau, or Looker
• 1+ years of experience applying statistics to strategic problems
• You are proficient in Python or R

Preferred Qualifications:

• Familiarity with Google BigQuery, AWS, or other big data environments
• 1+ years of experience with dbt
• Comfort with version control (Github, code review
• 1+ years of experience data modeling
• 1+ years of experience with data visualization tools such as Mode, Tableau, or Looker, Hex)
• Familiarity with using Gen AI–enabled tools for analytics and workflow acceleration (e.g., Claude Code, Cursor, Hex)

REQ-019879 

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems. 

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

• Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
• Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

• Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work: 

• Your ethos is ownership
• You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.
• You demonstrate strong judgment under uncertainty. 
• You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.
• You lead through clarity and active listening. 
• You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions. 
• You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope. 
• You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.
• You fall in love with the problem, not the solution
• You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem. 
• When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook. 
• You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

Location: Remote, New York City, or Oakland

• Travel of approximately one week per quarter may be required. 

Role Type: Full-time

Compensation:  $97,000

Visa sponsorship: Not available

Hires remotely in: United States

Experience: 2+ years

Recidiviz is thrilled to be hiring a Policy Data Analyst to join our team! We’re a small, fast-moving group that works with complex criminal justice data from our state partners and develops analyses and tools that target the drivers of incarceration. That’s where you come in. We’re looking for someone who has creativity and inquisitiveness to identify and solve open-ended problems, clarity to think through complex and variable data, flexibility to adjust in a rapidly evolving environment, and above all else, a collaborative, kind nature to add to our culture.

About us

Recidiviz is creating safer, healthier communities by improving outcomes for people in the criminal justice system. We build technology to reduce the number of people in prison and to help criminal justice leaders embrace data-driven decision-making. 

Using software tools and thoughtful product design, we’ve been able to safely and permanently reduce incarceration and improve outcomes. We work side-by-side with leaders of the criminal justice system, people in prison and on supervision, and ecosystem partners to build a better path forward. In addition to the revenue we earn from state partners, some of the most respected philanthropists and foundations support our work.

People who succeed at Recidiviz lead with kindness and humility, assume good intent, learn from failure, and fix problems when they see them. They are excited to work arm in arm with government leadership and staff to improve outcomes. They are great listeners. They build deep relationships with and empathy for the people we work with and the people who our mission serves, even when those two groups feel at odds. 

About the role

Recidiviz’s policy team supports state DOC leaders that want to rewrite old policies or implement new ones, rooted in evidence and analytics, to improve outcomes, increase public safety and community health, and drive meaningful changes. We tailor data analysis, built on detailed DOC data, to answer questions like: What combination of criteria best select for probation clients who are safe to discharge? What static factors influence parole decisions today and how would that change if new, dynamic factors were added? How many people would X, Y, or Z adjustment to a policy affect and what can we say about the affected group? By translating concepts into concrete modeling, we help drive smarter and more ambitious change.

This role collaborates across several teams to guide work that targets the drivers of incarceration. Our Policy Data Analysts work with diverse data – criminal justice data both raw and processed from across the country, reports and policy documents from government agencies, and much more – to develop the policy analyses that deepen our understanding of the criminal justice system and motivate policy change. Our Policy Data Analysts translate policy concepts into quantitative metrics, perform analyses, and play a key role in contextualizing and presenting their analyses to stakeholders, both internal and external. 

Travel of approximately one week per quarter may be required. 

Core responsibilities

• Leveraging criminal justice datasets to generate context-responsive insights that expand  momentum for policy reform
• Adapting analytical methods to evidence detailed policy concepts and quantify policy-design tradeoffs
• Contextualizing and communicating key findings to internal and external stakeholders
• Collaborating with our Data Science and Implementation Engineering teams to design and execute on targeted roadmaps that drive impact in the states where we work
• Collaborating with our Product Management and State Engagement teams to bring analyses and data modeling into administrative and legislative policy processes

Wild success

A year from now:

• You’ve driven impact. Your work has informed several policy reforms across the country and has helped quantify the impact those reforms are having on the outcomes of the justice system.
• You’ve leveled up our analytical team. Your contributions to our analytics and processes, as well as your support for your teammates, has helped set our team up to achieve more impact sooner.

Minimum qualifications

• Strong communication and collaboration skills, to help nurture a knowledgeable, data-oriented culture 
• Enthusiasm for working with internal and external partners from diverse backgrounds and worldviews, such as government staff, legislators, political consultants, researchers, journalists, technical staff, and practitioners in criminal justice reform
• Sufficient math or statistical background to reason about analysis design, examine results closely, and prepare data and analyses that are usable for various applications
• 2 or more years of practical experience exploring, analyzing, and processing complex datasets
• Professional work experience using SQL to work with large datasets, including high proficiency writing efficient queries for more complex data extraction and transformation tasks
• High familiarity with Python, specifically Pandas package, for tasks such as statistical analysis and data visualization

Preferred qualifications

• Ability to discern when and how analysis is actionable for stakeholders; ability to “wear your public servant hat” while conducting analysis
• Experience adapting quantitative methods that introduce intuitively meaningful metrics in ambiguous, unconstrained contexts
• Experience balancing depth and speed when navigating short timelines and shifting priorities
• Experience working with large datasets from the public sector, especially related to criminal justice
• Familiarity with our data stack, which includes Google Cloud Platform, BigQuery, Looker, Jupyter notebooks, and Python/Pandas

Compensation

Compensation is standardized based on roles and responsibilities. This ensures equitable compensation and responsible stewardship of our resources. As such, we do not negotiate compensation offers. 

The compensation for this role is: $97,000.

What we offer

• Effective, extremely thoughtful colleagues, working together on a mission that matters
• 90% medical, dental, and vision insurance coverage for you and your dependents
• Flexible time off, including 20 days of PTO, 3 days of paid volunteering time, and 13 paid holidays
• 12 weeks of paid parental leave
• 401(k) retirement plan with 5% company match and no vesting period
• Complimentary One Medical membership (depending on location)
• Partnership with Carrot to provide employees with inclusive fertility and family-forming benefits, as well as a small but growing number of hormonal health and gender-affirming care benefits
• Monthly ClassPass credit for personal wellness
• Free mental health support via Talkspace
• Well-located offices in Oakland and Manhattan, with the flexibility to work remotely or go into either office as you choose
• An annual company offsite each spring and other ad-hoc gatherings
• All the exhilarating challenges and stretch opportunities of a tech startup, combined with the mission-driven heart of a nonprofit

More about Recidiviz

Recidiviz was an all-volunteer effort until early 2019, when Clementine, Andrew, and Joshua founded the organization. Since then, we’ve built an A-team of software engineers, designers, product managers and domain experts, from companies like Google, Apple, Dropbox, Opower, and Sidewalk Labs. Recidiviz was part of Y-Combinator’s 2019 class and has received support from some of the most respected philanthropists and foundations, including Ford Foundation, Mackenzie Scott, Schmidt Futures, Arnold Ventures, Chan Zuckerberg Initiative, and the Mozilla Foundation.

Today, Recidiviz works with (and earns revenue from) over 18 state partners – big and small, red and blue – and covers more than 40% of the US incarcerated population. We have helped to get tens of thousands of people out of the criminal justice system, safely and equitably, and saved states nearly $1 billion. In the next five years, Recidiviz plans to partner with 40 states and help 250,000 people who are stuck in the system to get out and stay out. In addition to partnering with state Departments of Corrections, Recidiviz collaborates with and learns from partners – from organizations like the Correctional Leaders Association (CLA) to community based organizations and justice-impacted individuals, whose perspectives guide our work.

To learn more about how we do what we do, check out our 2024 Year in Review, read some press coverage, or watch our TED Talk. And if you’re really keen to see our work, you can dive into our Github :).

An important note

Lasting change is always built on diversity. Recidiviz recruits, employs, trains, compensates and promotes regardless of race, religion, color, national origin, sex, sexual orientation, disability, age, veteran status, ancestry, citizenship, marital status, gender identity and all protected status as required by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a special need that requires accommodation, please let us know in your application. Even if you don't think you meet all the criteria above, drop your resume, and we'll take a look – you might be great for another role or another time!

The Role

Our commercial segment — companies with up to 250 employees — is predominantly developer- and engineer-led. These buyers don't respond to decks and discovery scripts. They respond to someone who speaks their language, understands their architecture, and can help them think through a real problem. That's who we're hiring.

As a Commercial Account Executive at ClickHouse, you'll own the full sales cycle for inbound, product-led, and self-serve accounts in this segment. You'll engage with data engineers, platform teams, and technical founders at the moment they're evaluating ClickHouse for a real use case — and your job is to help them succeed, faster. The best deals in this segment don't feel like sales. They feel like an engineering consultation that ends in a contract.

Our commercial customers include companies like Circle, Flashbots, Blockworks, Cypress.io, Kit, Whop, Coframe, Shaped, and janitorai — developer-first products that chose ClickHouse because they needed something that could handle billions of events without slowing down their users. The best deals in this segment don't feel like sales. They feel like an engineering consultation that ends in a contract.

This is a role for technically strong people who are ready to own a number. Prior closing experience is not required — but technical credibility is non-negotiable.

What You Will Be Doing

• Own the full sales cycle from inbound lead to close for accounts in the sub-250 employee segment, with a focus on speed, technical depth, and conversion quality.
• Engage directly with data engineers, platform architects, and technical founders to understand their use cases, data volumes, query patterns, and infrastructure requirements — and map those to ClickHouse capabilities.
• Troubleshoot schema design questions, ingestion patterns, and integration challenges during the evaluation process; serve as a trusted technical advisor rather than a traditional sales rep.
• Identify expansion opportunities within the existing self-serve and product-led customer base; convert usage signals into meaningful commercial relationships.
• Partner with Solutions Engineers on more complex evaluations, and advocate for customer needs internally with Product and Engineering.
• Maintain rigorous pipeline hygiene — documenting technical context, decision criteria, stakeholders, and next steps in Salesforce so nothing falls through the cracks.
• Contribute to playbooks, technical objection handling guides, and onboarding materials that help the team scale what's working.
• Participate in developer community events, technical meetups, and online forums where our users naturally gather.

What You Bring

• A technical foundation that earns respect in engineering conversations — built through experience as a data engineer, solutions engineer/architect, software engineer, or similar role.
• Comfort with the modern data stack: columnar databases, streaming ingestion (Kafka, Kinesis), cloud infrastructure, and SQL-heavy analytics workflows. Hands-on experience with ClickHouse, DuckDB, Druid, Pinot, BigQuery, Snowflake, or similar is a strong plus.
• Some customer-facing experience — whether in pre-sales, technical account management, solutions engineering, or a customer-success capacity. You've navigated technical conversations with real stakes before.
• An instinct for moving quickly. This segment runs on short cycles. You know how to drive urgency without being pushy, and how to remove technical blockers that stall deals.
• Strong written and verbal communication. You can simplify complex concepts without dumbing them down, and you write clearly enough that your emails actually get responses from engineers.
• Curiosity about the business side of technology. You're interested in understanding why companies buy, not just what they're building.
• Ownership mentality. You're comfortable operating with autonomy, making judgment calls without a playbook, and learning from what doesn't work.

Why This Role Is Different

Most AE roles are execution roles. This one is a craft role. You'll build deep product knowledge, learn how high-growth companies architect for scale, and develop commercial skills in an environment where your technical instincts are your biggest competitive advantage. For the right person, this is a rare opportunity to bridge two worlds — and get paid competitively to do it.

The Data Engineering team builds tools and systems that make Gusto's data consistent, user-friendly, and helpful. This helps our teams make decisions using data and provide intelligent, customized experiences to our customers.

We're looking for a Senior Data Engineer who can take loosely defined problems and drive them end-to-end—from framing the problem and aligning stakeholders to designing, building, and delivering durable data solutions. You’ll partner closely with analytics, product, and engineering teams to deliver data solutions that drive real business and customer impact.

Preferred Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products
• Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Proven experience building and maintaining robust data pipelines and ETL workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
• Hands-on experience ingesting data from diverse sources, including APIs, databases, SaaS applications, and event streams.
• Strong foundation in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability to ensure reliability and trust in data systems
• Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
• Proven ability to optimize performance and cost across data workflows and storage systems
• Functional understanding of how to leverage AI and automation in data engineering — building self-service tools, intelligent pipelines, and agents that automate repetitive tasks
• Exemplar problem-solving skills and ability to work collaboratively in cross-functional teams.
• Strong communication and collaboration skills, with a focus on clarity, empathy, and shared ownership

Compensation Details

Our cash compensation amount for this role is targeted at $155,000-$185,000/yr in Denver, $170,000-$200,000/yr in Los Angeles, and $190,000-$220,000/yr for San Francisco, Seattle, and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.

The Department: Data

At Gemini, our Data Team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.

The Role: Principal Data Engineer

The Data Engineering Team owns the ingestion and transformation of data from production databases, streams, and external data sources into our data warehouse. As a Principal Data Engineer, you will set the technical direction for how data is modeled, processed, and delivered across the organization. You will partner closely with product, analytics, ML, finance, operations, and engineering teams to move, transform, and model data reliably, with observability, resilience, and agility. You’ll lead by example through design excellence, mentoring, and technical leadership, ensuring our data architecture is scalable, governed, and ready for the next generation of analytics and machine learning at Gemini. 

This is a senior individual contributor role — highly technical, strategic, and cross-functional — where you’ll influence the design of data systems that underpin key decisions and customer-facing products across Gemini.

This role is required to be in person twice a week at our New York City, NY office.

Responsibilities:

• Define and drive the long-term vision for data architecture, modeling, and transformation at Gemini
• Establish standards for data reliability, observability, and quality across all pipelines and data products using languages and frameworks such as Python, SQL, Spark, Flink, Beam, or equivalents
• Partner with Staff and Senior Data Engineers, Platform Engineers, and Analytics Engineers to unify how data is produced, stored, and consumed
• Lead large-scale design initiatives that span multiple teams and systems, ensuring maintainability, performance, and security
• Partner with data scientists, ML engineers, analysts, and product teams to understand data requirements, define SLAs, and deliver coherent data products that others can self-serve
• Establish data quality, validation, observability, and monitoring frameworks (data auditing, alerting, anomaly detection, data lineage)
• Investigate and resolve complex production issues: root cause analysis, performance bottlenecks, data integrity, fault tolerance
• Mentor and guide more junior and mid-level data engineers: lead code reviews, design reviews, and best-practice evangelism
• Help recruit and onboard new talent, shaping the future of Gemini’s data engineering discipline
• Stay up to date on new tools, technologies, and patterns in the data and cloud space, bringing proposals and proof-of-concepts when appropriate
• Document data flows, data dictionaries, architecture patterns, and operational runbooks

Minimum Qualifications:

• 10+ years of experience in data engineering (or similar) roles
• Strong experience in ETL/ELT pipeline design, implementation, and optimization
• Deep expertise in Python and SQL writing production-quality, maintainable, testable code
• Experience with large-scale data warehouses (e.g. Databricks, BigQuery, Snowflake)
• Solid grounding in software engineering fundamentals, data structures, and systems thinking
• Hands-on experience in data modeling (dimensional modeling, normalization, schema design)
• Experience building systems with real-time or streaming data (e.g. Kafka, Kinesis, Flink, Spark Streaming), and familiarity with CDC frameworks
• Experience with orchestration / workflow frameworks (e.g. Airflow)
• Familiarity with data governance, lineage, metadata, cataloging, and data quality practices
• Strong cross-functional communication skills; ability to translate between technical and non-technical stakeholders
• Proven experience in recruiting, mentoring, leading design discussions, and influencing data-engineering best practices across teams

Preferred Qualifications:

• Experience with crypto, financial services, trading, markets, or exchange systems
• Experience with blockchain, crypto, Web3 data — e.g. blocks, transactions, contract calls, token transfers, UTXO/account models, on-chain indexing, chain APIs, etc.
• Experience with infrastructure as code, containerization, and CI/CD pipelines
• Hands-on experience managing and optimizing Databricks on AWS

• Competitive starting salary
• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off

Salary Range: The base salary range for this role is between $192,500 - $275,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce.

At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.

#LI-AA1

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.

The Department: Data

At Gemini, our Data Team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.

The Role: Staff Data Engineer

The Data team is responsible for designing and operating the data infrastructure that powers insight, reporting, analytics, and machine learning across the business. As a Staff Data Engineer, you will lead architectural initiatives, mentor others, and build high-scale systems that impact the entire organization. You will partner closely with product, analytics, ML, finance, operations, and engineering teams to move, transform, and model data reliably, with observability, resilience, and agility.

This role is required to be in person twice a week at our New York City, NY office.

Responsibilities:

• Lead the architecture, design, and implementation of data infrastructure and pipelines, spanning both batch and real-time / streaming workloads
• Build and maintain scalable, efficient, and reliable ETL/ELT pipelines using languages and frameworks such as Python, SQL, Spark, Flink, Beam, or equivalents
• Work on real-time or near-real-time data solutions (e.g. CDC, streaming, micro-batch) for use cases that require timely data
• Partner with data scientists, ML engineers, analysts, and product teams to understand data requirements, define SLAs, and deliver coherent data products that others can self-serve
• Establish data quality, validation, observability, and monitoring frameworks (data auditing, alerting, anomaly detection, data lineage)
• Investigate and resolve complex production issues: root cause analysis, performance bottlenecks, data integrity, fault tolerance
• Mentor and guide more junior and mid-level data engineers: lead code reviews, design reviews, and best-practice evangelism
• Stay up to date on new tools, technologies, and patterns in the data and cloud space, bringing proposals and proof-of-concepts when appropriate
• Document data flows, data dictionaries, architecture patterns, and operational runbooks

Minimum Qualifications:

• 8+ years of experience in data engineering (or similar) roles
• Strong experience in ETL/ELT pipeline design, implementation, and optimization
• Deep expertise in Python and SQL writing production-quality, maintainable, testable code
• Experience with large-scale data warehouses (e.g. Databricks, BigQuery, Snowflake)
• Solid grounding in software engineering fundamentals, data structures, and systems thinking
• Hands-on experience in data modeling (dimensional modeling, normalization, schema design)
• Experience building systems with real-time or streaming data (e.g. Kafka, Kinesis, Flink, Spark Streaming), and familiarity with CDC frameworks
• Experience with orchestration / workflow frameworks (e.g. Airflow)
• Familiarity with data governance, lineage, metadata, cataloging, and data quality practices
• Strong cross-functional communication skills; ability to translate between technical and non-technical stakeholders
• Proven experience in mentoring, leading design discussions, and influencing data-engineering best practices across teams

Preferred Qualifications:

• Experience with crypto, financial services, trading, markets, or exchange systems
• Experience with blockchain, crypto, Web3 data — e.g. blocks, transactions, contract calls, token transfers, UTXO/account models, on-chain indexing, chain APIs, etc.
• Experience with infrastructure as code, containerization, and CI/CD pipelines
• Hands-on experience managing and optimizing Databricks on AWS

• Competitive starting pay
• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off

Salary Range: The base salary range for this role is between $168,000 - $240,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce.

At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.

#LI-AA1

What You’ll Do:

The Data Services Team builds and operates the data platform that powers CoreWeave's AI cloud, from transactional and analytical storage to streaming, metadata, and governance. We give our customers and CoreWeave engineers the primitives they need to ingest, store, process, and serve data at the scale and performance that next-generation AI workloads demand.

If you want to define how data flows across a rapidly scaling AI cloud, and turn that strategy into infrastructure others depend on, this is your team.

About the role:

As a Staff Product Manager for Data Services, you'll own the end-to-end strategy, roadmap, and execution for CoreWeave's data services portfolio: databases, data lakes, streaming, metadata and catalog, and data sharing and integration.

You'll shape a multi-year vision for how our data services underpin AI and GPU workloads, then lead delivery from 0 to 1 and 1 toN. That means working directly with strategic customers and partners, collaborating closely with engineering and GTM, evaluating emerging data technologies, and ensuring our services are secure, reliable, and easy to adopt.

The hardest problems you'll tackle are around scale, throughput, and performance for GPU-intensive applications, and you'll have real influence over the architecture to solve them.

In this role, you will own:

• Product strategy and roadmap across the data services portfolio, balancing near-term delivery with long-term bets
• Customer and partner engagement - diving deep into data architectures, co-designing solutions, and supporting large-scale deployments
• Cross-functional alignment with engineering, GTM, and leadership to drive clarity and execution in a fast-moving environment
• Market and competitive analysis to surface opportunities, validate priorities, and keep us ahead of the curve
• API-first platform thinking - partnering with architects on service designs, SLAs, and operational excellence

Who You Are: 

• 8+ years of product management experience in data platforms, databases, analytics, or cloud infrastructure, with at least 3-4 years focused on data services (managed databases, streaming, data warehouses, data lakes, or governance platforms)
• Technical fluency in:
• Relational and/or distributed databases (e.g., PostgreSQL, MySQL, SingleStore, Snowflake, BigQuery)
• Streaming and pipelines (e.g., Kafka, CDC, ETL/ELT, lakehouse architectures, real-time data sharing)
• Data security and governance (encryption, IAM/RBAC, data masking, network isolation, compliance)
• A track record of owning complex, API-first platform products from concept through multiple release cycles
• Strong communication skills - able to create clarity from ambiguity, influence without authority, and translate technical depth for any audience
• Comfort operating in a fast-paced, high-growth environment where the answer isn't always obvious

Preferred:

• Staff or Director-level PM experience at a database vendor, cloud provider, or high-growth infrastructure company
• Hands-on experience with managed data services on AWS, Azure, or GCP (e.g., RDS, Aurora, Cosmos DB, BigQuery)
• Background in hybrid or multi-cloud architectures: connectivity, data locality, replication
• Experience with AI/ML data products: feature stores, vector search, real-time analytics, or serving pipelines for LLM workloads
• Familiarity with SaaS/PaaS packaging and usage-based or tiered pricing models
• Prior engineering or architecture experience on data or distributed systems

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• Love building platforms that other teams and customers treat as critical infrastructure
• Are curious about new databases, analytics, and AI data patterns, and are good at separating real value from hype
• Can drive clarity in highly technical, ambiguous problem spaces and rally cross-functional teams around a plan
• Enjoy going deep with customers on their data architectures and co-designing solutions
• Balance long-term vision with fast iteration, and you don't need perfect information to move forward

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

About the Team: The Brand Ad Formats team drives the development of ad formats that help advertisers maximize reach and brand impact. They focus on high-visibility, awareness-driven solutions that create memorable experiences for Reddit users. By delivering guaranteed placements and engaging ad interactions, they support major brand initiatives and help advertisers achieve measurable outcomes.  The team is building fully customizable interactive formats and AI-driven ads that incorporate User-Generated Content (UGC).  Moving forward, we will be doubling down on Video Ads, with the goal of turning Reddit into an industry leader and a ‘must buy’ for advertisers to promote video content.

As a Staff Android Engineer, you will lead the technical strategy to turn Reddit’s Video Ads into a premier offering for brand advertisers.  You will also build and provide technical guidance on new reddit-unique ad formats on Android, ensuring they are high performance, high quality and scalable.

What you’ll do: 

• Video Ads Tech Lead: Partner closely with Product and Design to build a roadmap that will transform our Video Ads format into an industry leader in the space, and drive the technical design and execution of projects that turn the roadmap into reality.
• Technical Strategy: Provide guidance to the team working on building video ads as well as reddit-unique ad formats that scale to millions of users, by establishing Android best practices and providing design reviews.
• Full-Cycle Leadership: Drive the entire development lifecycle—from early-stage discovery and prototyping to testing, data-driven experimentation, and deployment.
• Raise the Bar: Mentor senior engineers across teams in ad formats and establish best practices for design, testing and operational excellence, while also leading by example in understanding and advocating for our customers.

What we expect from you: 

• 8+ years of software engineering experience (Staff level seniority). 
• Android Mastery: (Minimum of 3+ years) Deep expertise in Kotlin and modern Android architectural patterns.  Completed 4+ Android development projects from ideation to deployment in production.
• Prior experience in Ad Tech, building highly interactive/rich-media mobile experiences.
• Product Mindset: Proven track record of delivering user-facing features where UI polish and performance are critical. 
• System Design: Ability to navigate complex, data-intensive environments and build fault-tolerant client-side systems.
• AI: Experience leveraging GenAI tools to increase software engineering productivity.
• Experimentation/Analysis: Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc.
• Versatility: An openness to work across the stack when necessary and explore innovative approaches (e.g., AI/ML integration).
• Entrepreneurial spirit: You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity.
• Excellent communication skills: You must be able to collaborate with teams in a fully remote environment, and discuss complex topics with technical and non-technical audiences.
• An experienced technical leader with a strong track record of mentoring and uplifting team members technical skills and aptitude.
• Strong organizational skills, the ability to prioritize tasks and keep projects on schedule for the team.
• BS degree in Computer Science, similar technical field of study, or equivalent practical experience.

Bonus points:

• Experience working on Video Ads
• Experience working at a scaled peer company
• Experience with Jetpack Compose

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Our Senior Developer Advocates are technical leaders and mentors that anchor our team. They own projects from beginning to end, facilitating collaboration and enabling Datadog's community to solve real-world problems. With a focus on Data Observability, this role will enable our community of engineers around Datadog to be part of a movement of building better software. This is a unique opportunity to use both your engineering expertise and advocacy skills to shape the ever-evolving technological landscape.

What You’ll Do:

• Act as a subject matter expert for data observability on behalf of the Datadog advocacy and engineering teams
• Create content in one or more mediums to build Datadog's reputation as a leader in data engineering and observability e.g. building demos, public speaking, blogging, documentation, webinars, open source, research reports and more
• Partner with and coach internal product and customer engineering teams on effective public communication and presentations for the work they do
• Contribute to the product through feedback (bugs or product enhancements suggestions)
• Identify and pursue opportunities for events, programs, and other community-focused work that establishes trust with practitioners

Who You Are: 

You are a trusted technical expert who enjoys helping data practitioners understand, operate, and improve complex data systems in production. You bring deep, hands-on experience in one or more areas of modern data engineering, and you use that experience to provide clear context to both the community and internal teams.

You are not expected to be an expert in every area below. Instead, you bring depth in some and working familiarity across many, and you are comfortable connecting them into a coherent operational story.

• Data engineering & processing systems: You have built, operated, or supported production data pipelines using distributed processing systems such as Apache Spark or Databricks, and understand common failure modes, performance tradeoffs, and operational challenges in batch and hybrid pipelines.
• Data platforms & analytics systems: You have hands-on experience with analytics platforms such as Snowflake and BigQuery, including schema design, data modeling, SQL-based analysis, and reasoning about performance, cost, and access patterns in real-world environments.
• Streaming & event-driven data: You understand how data flows through streaming systems such as Kafka or similar platforms, including producer and consumer behavior, lag, delivery semantics, and how streaming issues propagate into downstream datasets and analytics.
• Data quality, lineage, and metadata concepts: You are familiar with how data teams reason about data quality, upstream and downstream impact, and change management, and have experience working with data lineage, metadata, or transformation tooling (for example dbt, OpenLineage, or related ecosystems), or have operated in environments where these concepts are core to reliability.
• Programming & querying: You are comfortable working in at least one programming language commonly used in data systems (for example Python, Scala, Java, or Go), along with strong SQL skills, and you can move fluidly between code, queries, and notebooks when exploring or demonstrating data systems.

You also have:

• 10+ years of experience as a software developer, data engineer, SRE, or other practitioner building and maintaining production systems
• 3+ years of experience in advocacy, developer relations, or equivalent experience reaching technical audiences through written content, conference talks, workshops, webinars, videos, or open-source contributions
• Publicly available writing samples, demos, repositories, or recordings of technical presentations
• Familiarity with modern cloud infrastructure and container-based systems
• A strong interest in self-directed learning and exploring new technologies, tools, and problem spaces

Bonus points:

• Experience supporting data pipelines for ML or AI systems
• Meaningful contributions to open source or shared technical tooling
  
  

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. 

Benefits and Growth: 

• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our Internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• Competitive global benefits

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Remote

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources
• Robust 401k program
• Employee Equity Plan
• Generous professional development allowance
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• 16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Employee Equity Plan
• Generous professional development allowance
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• We offer free German courses at beginning, intermediate and advanced
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

Scopely is looking for a Senior Product Analyst to join our Monopoly Go! team in the US on a remote basis. *This role requires the successful candidate to be based in the US Eastern Time Zone (ET) to support core working hours and team collaboration.

At Scopely, we care deeply about what we do and want to inspire play, every day - whether in our work environments alongside our talented colleagues, or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people around the world daily.

MONOPOLY GO! is a global phenomenon and the biggest mobile game launch in history, captivating millions of players worldwide. The team is based in Europe and the US, and works every day to create captivating new experiences for our players.

What you will do

As a Senior Product Analyst you will join a team of Product Analysts and Analytical Engineers, working to support one of our Vertical teams in collaboration with the wider analytics org. In this role, partnering with our internal data platform and data science teams, you will use data to generate player behavior insights and improve feature performance; from data modeling and event tracking, through to AB-testing, insightful analyses and recommendations that answer the game’s most complex and challenging questions. This is an individual contributor role, that has a lot of independence and responsibility, with building processes and taking end to end analytics projects

• Data Analysis: Dive deep into large, complex data sets to extract actionable insights that drive strategic decision-making. Analyze player behavior, game performance, and trends to inform product strategies and optimizations
• Game Team Support: Collaborate with stakeholders to identify opportunities and challenges to the specific game vertical.  Define key metrics, establish data collection processes, implement analytical frameworks and effectively communicate the insights to drive continuous improvement
• Ownership of Analysis: Take ownership of end-to-end analytical projects, from the inception of a new feature to ensure robust reporting and monitoring is in place, to design and assess A/B experimentation and deliver final insights, interpretations and presentations. 
• Drive the execution of analytical initiatives with precision and attention to detail
• Cross-functional Collaboration: Work closely with teams across the organization, to translate data insights into impactful business outcomes.
• Product Roadmap Influence: Partner to shape the future direction of the game
• Digging Deep: Hands-on exploration into existing reports and data, correlation of KPIs, definition of success for the Vertical, to identify the needs and gaps and actively work towards the improvements. Leverage data-driven insights to prioritize features, optimize game economies, and refine product roadmaps for maximum player engagement and satisfaction
• Presentation and Communication: Effectively communicate complex findings and recommendations to stakeholders at all levels of the organization. Present insights in a clear, concise manner through compelling presentations and reports

What We’re Looking For

• Passion for continuous learning in a fast-paced, highly-collaborative environment
• Excellent English communication skills, written and verbal
• Intellectual curiosity and analytical rigor
• 4+ years of experience as a Data Analyst or Business Intelligence related role. Gaming industry background is an advantage.
• Solid knowledge of SQL and comfort working with large data sets – exposure with BigQuery and Python/R experience a plus
• Working Knowledge of visualization tools: Looker (Preferred), Qlikview, Tableau or PowerBI
• Strong presentation skills; ability to communicate complex results throughout an organization
• A love for or strong desire to work with mobile games

At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that! We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure!

Why this role?

Warp is hiring an Analytics Engineer to own the data vertical — a high autonomy role at the center of how we understand our product, users, and business. You'll work across every function at Warp: product, engineering, growth, revenue, and go-to-market.

Warp is a fast-growing AI developer tool. Our data footprint reflects that growth — we ingest telemetry from our apps and servers, LLM conversational data, transactional production databases, GTM pipelines, and a range of third-party sources. Your job is to turn that raw data into the reliable metrics and deep insights that drive real decisions.

This isn't a role where you slot into an existing system. You'll own the data model, define how we measure what matters, and set the standard for how analytics gets done at Warp. That means building durable infrastructure and shipping high-impact analysis — often at the same time.

If you want to shape how a company at scale thinks about its data from the ground up, this is that role.

As an Analytics Engineer, you will...

This is a full-stack data role that moves across the data stack and touches all parts of Warp’s business. Your work will fall into three broad areas:

Operations

• Define, build, and visualize core product and business metrics
• Design and analyze A/B experiments to measure the impact of product changes
• Adapt data models to support new product features, pricing models, and business initiatives
• Partner with GTM teams to surface product-qualified leads, measure engagement, and support billing and revenue analytics

Infrastructure

• Build and maintain canonical data models that serve as reliable sources of truth
• Write production ETL to ingest new data sources and reverse-ETL to push data to downstream consumers
• Develop AI agents to automate pieces of the data team’s workflows
• Establish data quality monitoring and reliability standards
• Build tooling that enables self-serve analytics across the company

Research

• Conduct deep ad-hoc analysis to understand user behavior, model business mechanics, and uncover growth opportunities
• Dig into questions like: How does Warp expand within companies? What is the optimal pricing structure? How do we identify potential enterprise leads? What characteristics of AI interactions drive churn?

You May Be A Good Fit If...

• You have 6+ years of experience in an analytics-focused data role
• You’re highly fluent in SQL and dbt on top of a modern warehouse like BigQuery, Snowflake, or Redshift
• You’ve built dashboards and visualizations with BI tools like Hex, Looker, Mode, Tableau, or Metabase
• You care deeply about the business decisions your data informs—not just building the pipelines behind them
• You balance business intuition with an engineering mindset: writing efficient, scalable queries; thinking about cost and compute across the data stack; and working with version control, CI/CD, and testing
• You have a bias for action and are comfortable operating with autonomy—you can identify opportunities across the company and proactively build solutions
• You’re an effective and creative communicator who can translate complex analysis into actionable insights for stakeholders with varying levels of data fluency
• You’re deeply curious—when a metric moves unexpectedly, you dig until you understand why
• You’ve integrated AI into your daily workflows; at Warp we lean heavily on agents to accelerate and automate our work

Bonus:

• Experience with the GCP data stack (GCS, BigQuery, Dataflow, Dataproc)
• Production-grade experience with Python
• Experience on a data team at an early-stage startup
• Familiarity with Warp’s platform

At Warp, we are dedicated to building a diverse, inclusive, and authentic workplace. So if you’re excited about this role, but your past experience doesn’t align perfectly with every qualification in this job description – we encourage you to apply anyways! We are a community of curious learners, and most of us are learning some skills for the first time (like our engineers learning to program Warp in Rust). You might be just the right candidate for this or other roles.

If you're feeling playful, try out our optional hiring challenge and submit your answers with your application: https://github.com/warpdotdev/hiring-challenge

Salary Transparency

Total compensation at Warp consists of two parts: 1) a competitive base salary, and most importantly, 2) meaningful equity.

When we find the right person, we try to put our best foot forward with an offer that excites you. We consider what you’d like to be paid, the skills and level of experience you bring, what similar jobs pay, and make sure there’s equal pay for equal work among those you’ll be working with. The budgeted compensation amount for this role is targeted at $180,000 - $210,000.

In addition to salary, all employees receive further compensation in the form of equity in the company. This is a meaningful stock option grant with a four-year vesting period and one-year cliff. Your equity is where most of the significant upside potential is. Comparing startup equity is always a bit tricky, so we’re happy to walk you through different valuation scenarios at the offer stage in order to help paint a clearer picture of the upside.

Final total compensation is determined by multiple factors including your experience and expertise and may vary from the amounts listed above.

What We Offer

• Competitive Salary & Meaningful Equity – we will stretch to get the right talent on board
• Full Medical, Dental, and Vision Benefits for employees (80% coverage for dependents)
• Flexible remote-first culture, with optional office spaces in NYC and SF for folks who want to work together IRL 
• Pre-tax FSA Health Savings Plan
• Pre-tax Commuter Benefit
• 20-days of Paid Time Off
• Unlimited Sick Time Off
• 12 US Holidays
• 16 weeks of paid Parental Leave for both birthing and non-birthing parents
• Twice-a-year company retreats
• Monthly gym and internet stipend
• Guideline 401(k)
• Complimentary OneMedical membership

Individuals seeking employment at Warp are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

The Role: WorldQuant is seeking an exceptional individual be a key contributor to the maturation phase of several essential software systems currently in firm wide use.  These systems are an important part of the research and production trading pipelines.  Your mission will be to relentlessly improve their performance, scalability, reliability and survivability while continuing to develop features.  The successful candidate will work with and provide mentorship and additional technological leadership.  Key technologies for the products include:

• Java (and to a lesser extent Python)
• Distributed systems
• Kafka
• PostgreSQL
• BigQuery

What You’ll Bring:

• Computer Science degree (advanced degree or equivalent experience preferred- particularly with storage technologies or distributed systems)
• Extensive experience as a key contributor in the development of complex software systems (leading financial services firm experience preferred- particularly involved in high performance systems)

Our Benefits:

Core Benefits:

• Fully paid medical and dental insurance for employees and dependents, flexible spending account, 401k, fully paid parental leave, generous PTO (paid time off) that consists of:
• Twenty vacation days that are pro-rated based on the employee’s start date, at an accrual of 1.67 days per month, three personal days, and
  ten sick days.
• Perks: Employee discounts for gym memberships, wellness activities, healthy snacks, casual dress code
• Training: learning and development courses, speakers, team-building off-site
• Employee resource groups

Pay Transparency:

WorldQuant is a total compensation organization where you will be eligible for a base salary, discretionary performance bonus, and benefits.

To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state.  We set standard base pay ranges for all roles based on job function and level, benchmarked against similar stage organizations.  When finalizing an offer, we will take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.

The Base Pay Range For This Position Is $150,000 – $250,000 USD.

At WorldQuant, we are committed to providing candidates with all necessary information in compliance with pay transparency laws.  If you believe any required details are missing from this job posting, please notify us at WQHR_US@WorldQuant.com, and we will address your concerns promptly.

By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction.

#LI-RS1

Position Summary: 
We are seeking a highly analytical and collaborative Manager to support and grow our Analytics team. This role requires strong technical skills in data analysis along with the ability to manage projects and support cross-functional teams. The ideal candidate will have experience mentoring analysts, managing business-critical requests, and contributing to a scalable data foundation that drives decision-making. This individual will play a key role in promoting efficiency, consistency, and innovation across our Analytics team.

Why you'll love working here:

• Our work makes a difference. We are a highly motivated team of specialists on a mission to improve the U.S. healthcare system for over 5 million members.
• We value diverse perspectives. We bring our full, authentic selves to a culture that values high performance and genuine connection.
• We are scaling fast. We are a rapid-growth organization with a strong financial outlook, affording stability while paving the way for innovation and creativity at every turn.

Key Responsibilities:  

Team Support & Project Management 

• Help set and track priorities, ensuring delivery of key analytics projects aligned with business goals. 

• Support the adoption of analytics best practices and tools through training sessions and knowledge sharing. 

• Coach data analysts within the team, contributing to their professional development and fostering a collaborative team environment. 

Data Execution & Optimization 

• Contribute to the execution of data analytics initiatives that align with business needs. 

• Collaborate on the development of scalable processes for data collection, analysis, and reporting. 

• Identify areas for improving efficiency through process improvements, automation, and better data practices. 

• Maintain documentation of key analytics processes and ensure data quality standards are upheld. 

Insights & Analysis 

• Conduct data modeling and analysis to generate insights that inform business strategy and process improvements. 

• Translate complex analytical findings into clear, actionable recommendations using visualizations and presentations. 

• Contribute to proactive analytics that support operational and strategic decision-making. 

Stakeholder Collaboration & Communication 

• Partner with product managers, business leaders, and clients to understand analytics needs and prioritize requests accordingly. 

• Proactively manage and foster stakeholder relationships by acting as a strategic, consultative advisor with a keen understanding of business objectives. 

• Advocate for data-driven decision-making across teams and leadership. 

Compliance and Quality Assurance 

• Ensure adherence to company compliance standards, including reporting any noncompliance. 

• Support the development and implementation of quality controls and departmental standards to satisfy organizational and regulatory requirements. 

• Participate in internal training sessions to support continued learning and development. 

• Responsible for adherence to the Capital Rx Code of Conduct, including reporting of noncompliance. 

Qualifications & Experience:  

• 4-6 years of experience in data analytics, business intelligence, or a related field. 

• Experience in PBM, health plans, healthcare, or Medicare. 

• Familiarity with pharmacy claims data, medical claims data, and client reporting metrics. 

• Expertise in SQL, Python, or R for data analysis, with strong coding hygiene and documentation practices. 

• Ability to perform complex analyses and synthesize findings into business insights. 

• Track record of partnering closely with internal and external stakeholders to provide consultative analytics support, proactively advising on business opportunities. 

• Working knowledge of data engineering fundamentals and working with cloud-based data warehouses (e.g., Snowflake, BigQuery, Redshift). 

• Proven ability to prioritize and manage multiple projects in a fast-paced environment. 

• Excellent communication and stakeholder management skills, with the ability to present complex data insights to executives. 

Preferred Qualifications:  

• Experience working in large-scale, high-growth organizations. 

• Knowledge of machine learning or advanced statistical modeling techniques. 

• Familiarity with Agile project management methodologies. 

• Master’s degree in Computer Science, Actuarial Science, Statistics, Economics, or a related field. 

• GitHub and dbt experience. 

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

About the Role: 

AlphaSense is seeking a highly analytical, entrepreneurial Data Analyst, Product Strategy & AI to serve as the analytical engine for our Product Management team and own our most important product analytics questions.

Our foundational data engineering and reporting are expertly managed by our technical team in India. We are hiring this NYC-based role to be the "connective tissue" between our raw data and our strategic product decisions. You will not be spending your days building traditional dashboards; instead, your mission is twofold:

1. Deep Strategic Analysis: Tackle our most complex product questions (e.g., understanding the true impact of our GenAI features on WAU/DAU retention and user habit formation).

2. AI-Native Data Democratization: Architect the infrastructure that allows our PMs to query our BigQuery database using natural language. You will be the tip of the spear in transitioning our product analytics model from a "request-and-wait" dashboard culture to a real-time, AI-empowered ecosystem.

Who You Are:

• Deep Product & Business Intuition: Demonstrated ability to understand product strategy and key metrics
• Experience: 8+ years of experience working in Product Analytics, Data Analytics, or equivalent roles
• Communication & Influence: Exceptional written and verbal communication skills, with a proven track record of presenting complex data insights clearly and persuasively to both technical and non-technical stakeholders. Proven ability to build strong working relationships and influence decision-making across cross-functional teams, particularly with Product Management.
• The "Stats-First" Mindset: As AI makes querying easier, knowing which statistical tests to apply and how to interpret the noise is your superpower.
• Technical Fluency (SQL & AI): Expert-level SQL is a must. You don't need to be a core software engineer, but you must be comfortable using Python and working with APIs, LLMs, and agentic frameworks.
• Curiosity & Adaptability: The AI tooling landscape changes rapidly. You are the kind of person who actively explores new frameworks, and experiments with how to apply them to business problems.
• Collaborative Leadership: Ability to work seamlessly with a highly technical remote data team (India) while acting as the strategic face of data for the product leadership team (NYC).
• Location & Alignment: Ability to effectively collaborate and interact in real-time with Product teams primarily based in NYC, while also being able to work effectively with a team in India.

What You’ll Do: 

• Be the Strategic Co-Pilot for PMs: Co-locate with the Product team to understand the business deeply. Proactively look across all product features to identify trends, drop-offs, and opportunities that go beyond feature-by-feature reporting. Lead the effort to translate complex data analysis into clear, concise, and compelling narratives that drive key business decisions and product feature development decisions. 

• Deep-Dive Analysis: Conduct and oversee comprehensive, complex analyses of product usage and adoption. Go beyond surface-level metrics to identify root causes for trends.

• Project Oversight: Act as a thought partner to Product leadership, proactively identifying opportunities and risks through data analysis. Collaborate closely with Product Managers to define key performance indicators (KPIs), establish success metrics for new features, and provide ongoing, proactive insights into product performance.

• Solve High-Stakes Business Questions: Use advanced statistical methods (e.g., cohort analysis, propensity matching, causal inference, etc.) to answer critical executive and investor questions—such as whether new product capabilities are actually inflecting long-term user retention.

• Build the AI-to-Data Bridge: Wire up our BigQuery data warehouse to modern LLMs using standard protocols (like Model Context Protocol / MCP) or native cloud AI tooling.

• Design the Semantic Layer: Partner with our Data Engineering team in India to ensure our data schemas are "AI-ready" (e.g., clean, well-aliased, and structured)

Why Join Us?

You will be the founding member of our next-generation analytics workflow, with the autonomy to define how a modern Product team interacts with data.

You love the story that data can tell. We are looking for an experienced Product Analyst who balances technical excellence with strong product intuition. You’ll be responsible for the full spectrum of data storytelling—from overseeing data ingestion and refining semantic models to providing deep-dive quantitative analysis on feature engagement, adoption funnels, and business impact.

You will deliver insights through concise dashboards, detailed reports, and emerging conversational interfaces. This is a high-impact role where you will partner directly with Product leaders and Engineers to influence the direction of our platform, transforming raw event data into the insights that fuel our next phase of scale.

WHAT YOU’LL DO:

• Drive Insight Strategy: Proactively identify the reports, dashboards, and deep-dive analyses required to move the needle on product goals
• Build & Scale: Design and implement robust data models and visualizations that serve as the "source of truth" for the Product organization
• Analyze at Scale: Navigate and extract meaning from billions of mobile and digital messaging data points
• Full-Stack Analysis: Get "in the weeds" to pull, clean, and transform raw data into sophisticated findings, ensuring data integrity at every step
• Influence Roadmap: Present findings to Product and Engineering leadership to directly inform feature prioritization and strategy

WHO YOU ARE:

• Experienced: 5+ years in BI, Data Analysis, and Data Modeling, ideally within a B2B SaaS or high-growth tech environment
• SQL Expert: 5+ years of experience writing complex, performant queries
• Technical: Proficient in programming or scripting languages (Python or R) for data manipulation and analysis
• Visual Storyteller: Expert-level experience with modern visualization tools (e.g., Looker, Tableau, Databricks)
• Scientifically Minded: BA/BS in Statistics, Math, Economics, Computer Science, or a related technical discipline; firm grasp of advanced statistical techniques
• Curious & Autonomous: A fast learner and self-starter who doesn't wait for a ticket to find an answer

Ideally, you'll have: 

• Modern Data Stack Flow: Experience with dbt, Airflow, or modern cloud warehouses (Snowflake/BigQuery)
• NoSQL Familiarity: Experience querying NoSQL databases like MongoDB or Redis
• AI/LLM Interest: Experience using Claude Code, GitHub Copilot, or other LLM harnesses to accelerate development and insight generation
• Cross-Functional Leadership: A proven track record of working across departments to align data strategy with business needs

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $90,000 and $135,000/year with an expected On Target Earnings (OTE) between $104,000 and $156,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

You love the story that data can tell. We are looking for an experienced Product Analyst who balances technical excellence with strong product intuition. You’ll be responsible for the full spectrum of data storytelling—from overseeing data ingestion and refining semantic models to providing deep-dive quantitative analysis on feature engagement, adoption funnels, and business impact.

You will deliver insights through concise dashboards, detailed reports, and emerging conversational interfaces. This is a high-impact role where you will partner directly with Product leaders and Engineers to influence the direction of our platform, transforming raw event data into the insights that fuel our next phase of scale.

WHAT YOU’LL DO:

• Drive Insight Strategy: Proactively identify the reports, dashboards, and deep-dive analyses required to move the needle on product goals
• Build & Scale: Design and implement robust data models and visualizations that serve as the "source of truth" for the Product organization
• Analyze at Scale: Navigate and extract meaning from billions of mobile and digital messaging data points
• Full-Stack Analysis: Get "in the weeds" to pull, clean, and transform raw data into sophisticated findings, ensuring data integrity at every step
• Influence Roadmap: Present findings to Product and Engineering leadership to directly inform feature prioritization and strategy

WHO YOU ARE:

• Experienced: 5+ years in BI, Data Analysis, and Data Modeling, ideally within a B2B SaaS or high-growth tech environment
• SQL Expert: 5+ years of experience writing complex, performant queries
• Technical: Proficient in programming or scripting languages (Python or R) for data manipulation and analysis
• Visual Storyteller: Expert-level experience with modern visualization tools (e.g., Looker, Tableau, Databricks)
• Scientifically Minded: BA/BS in Statistics, Math, Economics, Computer Science, or a related technical discipline; firm grasp of advanced statistical techniques
• Curious & Autonomous: A fast learner and self-starter who doesn't wait for a ticket to find an answer

Ideally, you'll have: 

• Modern Data Stack Flow: Experience with dbt, Airflow, or modern cloud warehouses (Snowflake/BigQuery)
• NoSQL Familiarity: Experience querying NoSQL databases like MongoDB or Redis
• AI/LLM Interest: Experience using Claude Code, GitHub Copilot, or other LLM harnesses to accelerate development and insight generation
• Cross-Functional Leadership: A proven track record of working across departments to align data strategy with business needs

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $90,000 and $135,000/year with an expected On Target Earnings (OTE) between $104,000 and $156,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

You love the story that data can tell. We are looking for an experienced Product Analyst who balances technical excellence with strong product intuition. You’ll be responsible for the full spectrum of data storytelling—from overseeing data ingestion and refining semantic models to providing deep-dive quantitative analysis on feature engagement, adoption funnels, and business impact.

You will deliver insights through concise dashboards, detailed reports, and emerging conversational interfaces. This is a high-impact role where you will partner directly with Product leaders and Engineers to influence the direction of our platform, transforming raw event data into the insights that fuel our next phase of scale.

WHAT YOU’LL DO:

• Drive Insight Strategy: Proactively identify the reports, dashboards, and deep-dive analyses required to move the needle on product goals
• Build & Scale: Design and implement robust data models and visualizations that serve as the "source of truth" for the Product organization
• Analyze at Scale: Navigate and extract meaning from billions of mobile and digital messaging data points
• Full-Stack Analysis: Get "in the weeds" to pull, clean, and transform raw data into sophisticated findings, ensuring data integrity at every step
• Influence Roadmap: Present findings to Product and Engineering leadership to directly inform feature prioritization and strategy

WHO YOU ARE:

• Experienced: 5+ years in BI, Data Analysis, and Data Modeling, ideally within a B2B SaaS or high-growth tech environment
• SQL Expert: 5+ years of experience writing complex, performant queries
• Technical: Proficient in programming or scripting languages (Python or R) for data manipulation and analysis
• Visual Storyteller: Expert-level experience with modern visualization tools (e.g., Looker, Tableau, Databricks)
• Scientifically Minded: BA/BS in Statistics, Math, Economics, Computer Science, or a related technical discipline; firm grasp of advanced statistical techniques
• Curious & Autonomous: A fast learner and self-starter who doesn't wait for a ticket to find an answer

Ideally, you'll have: 

• Modern Data Stack Flow: Experience with dbt, Airflow, or modern cloud warehouses (Snowflake/BigQuery)
• NoSQL Familiarity: Experience querying NoSQL databases like MongoDB or Redis
• AI/LLM Interest: Experience using Claude Code, GitHub Copilot, or other LLM harnesses to accelerate development and insight generation
• Cross-Functional Leadership: A proven track record of working across departments to align data strategy with business needs

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $90,000 and $135,000/year with an expected On Target Earnings (OTE) between $104,000 and $156,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

About The Role

The Senior Manager, Regional Advisor Success - West owns market level performance across Fora’s west markets, including advisor growth, productivity, product adoption, and retention. This role introduces a geographic operating layer to Fora’s advisor business, with full accountability for market outcomes. It is responsible for defining what strong market ownership looks like, building the systems to track performance, and driving interventions that improve results. This role works closely with cross functional partners while independently setting and executing a market strategy.

Key Responsibilities

• Own performance across all US West markets, including advisor growth, engagement, and retention, with clear accountability for outcomes.
• Develop and deliver regular market performance reporting that surfaces trends, identifies gaps, and informs action.
• Identify underperforming markets, diagnose root causes, implement targeted interventions to improve outcomes, and scale what works.
• Serve as Fora's local presence in key markets - attend industry events, cultivate referral pipelines through Pro advisors, and drive advisor acquisition in target cities
• Coach and enable top advisors.
• Collaborate cross functionally with teams including Events, Travel Partners, Community, Training, and Product to ensure market needs are represented and supported.

Requirements

• 4-8 years of professional experience in roles such as field or regional operations, multi market customer success, or strategy and operations within a marketplace, membership organization, or multi unit business
• Demonstrated ownership of market or regional outcomes tied to measurable business results such as revenue  growth, conversion rates, productivity metrics, or unit economics
• Experience managing multiple markets, accounts, or locations simultaneously, with the ability to operate at both strategic and execution levels
• Proven ability to influence and drive alignment across cross functional stakeholders without direct authority
• Strong data fluency, including experience building or using dashboards and translating data into actionable insights
• Clear and structured communication skills, with the ability to synthesize information and drive decisions

Strongly Preferred

• Experience in marketplace, hospitality, fitness, or other multi location or community driven businesses
• Background in consulting, strategy, or operations with hands-on implementation experience
• Sales enablement or sales coaching experience
• Familiarity with data tools such as SQL, BigQuery, Looker, or similar platforms
• Experience using AI tools to support analysis, decision making, or operational workflows
• Exposure to community building, events, or engagement focused roles
• Prior people management experience is helpful but not required

Compensation

Compensation for this role varies based on experience, with an indicative range of $140K–$180K + equity. Final compensation will depend on the level at which the candidate is hired, as we’re considering multiple levels for this role.

• Unlimited vacation
• Health Insurance (including an option completely covered by Fora HQ)
• Dental & Vision Insurance
• Wellhub Memberships
• 401k plan with company match
• Commuter Benefits
• Supplemental Life Insurance
• Stock Options

This is a remote role based in Los Angeles, with occasional travel to our New York City office.

Software Engineer, Machine Learning (MLOps & Data)

A Career with Point72’s Surveillance Team

On the Knowledge Graph Intelligence team, you’ll work alongside product managers, engineers, and data scientists to build the next generation of intelligent systems through graph technology. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision-making and enhance how we build and operate our platforms and applications.

What you’ll do

In this data-heavy role, you will design and build mission-critical infrastructure that powers our machine learning lifecycle, from large-scale data processing and feature engineering to model training, real-time deployment, and monitoring. Specifically, you will:

• Architect and implement the full lifecycle of ML models, from data ingestion to production inference, contributing to the design of our next-generation, event-driven architecture, using technologies like gRPC, Kafka, and high-performance API frameworks, like FastAPI, Spring WebFlux, and Axum.
• Engineer and automate robust, large-scale data processing pipelines (ETL/ELT) using tools like Spark, dbt, and workflow orchestrators, and lead the design and implementation of our Feature Store strategy.
• Own the MLOps framework for model training, versioning, and deployment, including CI/CD pipelines, automated workflows, and experiment tracking and evaluation tooling.
• Implement sophisticated deployment strategies, including canary, blue-green, shadow, and A/B testing, to ensure safe, zero-downtime releases, and optimize inference performance for LLMs and other large models.
• Leverage cutting-edge tools and techniques like quantization and compilation to maximize throughput and minimize latency.
• Collaborate with data scientists to develop models and optimize model performance for low-latency serving using techniques like Python performance tuning.
• Define, provision, and manage our cloud infrastructure using Terraform, working hands-on with a wide array of cloud services across compute, storage, and machine learning platforms.

What’s REQUIRED

• 5+ years of experience in a software, data, or ML engineering role.
• Strong proficiency in SQL.
• Experience building and orchestrating data pipelines using tools such as Spark, dbt, and Dagster/Airflow, as well as data warehouses like Snowflake, Redshift, BigQuery.
• Understanding of infrastructure as code, including experience with Terraform.
• Proficiency with containerization and orchestration including Docker and Kubernetes.
• Hands-on experience with CI/CD tools and ML lifecycle tools, including Jenkins, MLflow, Kubeflow, and W&B.
• Experience with AWS and its core services including S3, EC2, Lambda, RDS, and EMR, and practical experience with Boto3 and AWS ML services SageMaker and Bedrock.
• Understanding of modern ML models and ability to discuss the performance characteristics and engineering trade-offs that influence deployment decisions.
• Experience with systems incorporating Graph Neural Networks (GNNs), recommendation systems, anomaly detection, and complex time-series models.
• Commitment to the highest ethical standards.

We take care of our people

We invest in our people, their careers, their health, and their well-being. When you work here, we provide:

• Fully-paid health care benefits
• Generous parental and family leave policies
• Volunteer opportunities
• Support for employee-led affinity groups representing women, people of color and the LGBT+ community
• Mental and physical wellness programs
• Tuition assistance
• A 401(k) savings program with an employer match and more

About point72

Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit https://point72.com/.

The annual base salary range for this role is $175,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Mercury is redefining *banking for ambitious companies and behind every great financial platform is a data system that people can actually trust.

As Mercury scales, our revenue systems generate an enormous amount of information: signals from remote and in-person meetings, automation tools, product usage, lifecycle events, and analytics pipelines. Turning that activity into clear, reliable intelligence — without brittle pipelines or constant rework — is critical to how we grow.

We’re looking for a Data Strategy & Operations leader to own the data foundations that power revenue execution. This role ensures that revenue data is reliable, interpretable, scalable, and usable as the business evolves and that teams can act on what they see with confidence.

In this role, you will report to the Head of Platforms & Infrastructure and play a central role in shaping how Mercury models, governs, and operationalizes GTM data. You’ll partner closely with Data Engineering, Data Science, Solution Architecture, Platform Engineering. etc.

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Here are some things you’ll do on the job:

• Own the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)
• Serve as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows
• Design and evolve core GTM data models across Salesforce, ETL, and analytics layers
• Partner with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers
• Partner with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates
• Own clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity
• Define and uphold data quality, freshness, consistency, and documentation standards for revenue platforms
• Monitor and improve pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations
• Identify opportunities to automate manual or error-prone data workflows and reduce operational overhead
• Act as a data thought partner to Platforms & Infrastructure, Revenue Operations, Analytics, and Security — advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives

You Should:

• Have 7+ years of experience in data engineering or data systems roles within SaaS or technology companies
• Have deep experience designing and operating production data pipelines
• Be highly proficient in SQL and experienced in data modeling
• Have hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift)
• Have experience with ETL / ELT tooling (e.g., dbt, Airflow, Census, or similar)
• Understand Salesforce data models and common GTM system architectures
• Be able to translate business concepts into durable, well-structured data models
• Communicate clearly with both technical and non-technical partners

Preferred:

• Experience supporting revenue, sales, or customer lifecycle data
• Familiarity with event-based data platforms (e.g., Data Cloud or equivalents)
• Experience working alongside platform engineering and security teams
• Exposure to data governance, access controls, and compliance considerations
• Experience mentoring or guiding other data practitioners

Compensation:

The total rewards package at Mercury includes base salary, equity, and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $158,400 - $198,000
• US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $142,600 - $178,200
• Canadian employees (any location): $149,700 - 187,100 CAD

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

[Please see the independent bias audit report covering our use of Covey for more information.] 

#LI-SN1

We are looking for a technically skilled, self-motivated, customer-focused manager to lead a team of high energy Support Engineers. In this role you will be responsible for hiring, developing and mentoring team members as well as delivering against key performance metrics. You'll lead process improvements for customer and partner growth, retention, and excellence, while fostering individual contributions and driving cross-functional projects that spark innovation and collaboration. You need to be comfortable working in a fast paced environment and continuously challenge the team to step outside their comfort zone.

Minimum Education Requirement

This position requires a U.S. Bachelor's degree (or foreign equivalent) in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related technical field. This requirement is a minimum and cannot be substituted by work experience alone.

What You Will Be Doing

• Become a product expert. We are a data driven group and expect you to become fully proficient in Sigma.
• Lead a team of exceptional product experts providing the Sigma user base with an excellent customer experience.
• Hire, develop and train a strong team of Support Engineers on an ongoing basis.
• Collaborate with cross-functional groups — Engineering, Design, Product, Customer Success, Sales, and Marketing ensuring delivery of a great customer experience.
• Manage and develop a strategy toward key metrics: CSAT, Initial Response (IR), SLA, Time to Resolution (TTR).
• Continuously refine processes to optimize efficiency, elevating customer support operations.
• Uncover golden insights within Support data, translating them into actionable strategies for continuous improvement.
• Develop a reputation for excellence, high credibility and integrity with peers across the org.

Qualifications We Are Looking For

• 5+ years of industry experience supporting data platforms in an enterprise environment and 2+ years in a people management role.
• Computer Science fundamentals. Strong domain expertise in databases and business intelligence.
• Comfortable with CDW environment/concepts.
• Proficient in SQL and data modeling concepts.
• A proven track record of building trust with customers and bringing issues to resolution quickly.
• Are curious, love to learn and to dig into new technologies and can pick them up quickly.
• Excellent verbal and written communication skills.

Highly Desirable Skills & Experience

• Managed a team supporting a SaaS product.
• Experience working with Snowflake, Redshift, or BigQuery.
• Knowledge of GCP or AWS.
• Startup experience.

Additional Job details

The base salary range for this position is $140k - $170k annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.

Sigma is growing rapidly, and our Technical Support Engineering team is scaling alongside it to meet the needs of an expanding global user base. As a Technical Support Engineer at Sigma, you will be part of an award-winning team recognized with the 2024 Stevie Gold Award for Customer Service, helping customers solve technical, business, and data challenges using the Sigma platform. You'll work closely with Product, Engineering, and Go-to-Market teams to diagnose complex issues, drive solutions, and contribute to the continuous improvement of our product and support operations.

Minimum Education Requirement

This position requires a U.S. Bachelor's degree (or foreign equivalent) in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related technical field. This requirement is a minimum and cannot be substituted by work experience alone.

What You Will Be Doing

• You will work with Sigma's customers and the pre-sales team to assist with the diagnosis and resolution of complex technical issues.
• Working closely with the development team, you will develop best practices and tools for diagnosing issues and optimizing the service for performance.
• Collaborate with cross-functional groups — backend, frontend, DevOps, design, product, and the go-to-market teams to create a first-class experience for users of our product.
• Participate in quarterly projects and perform periodic on-call duties to improve automation and processes.

Qualifications We Are Looking For

• 2+ years of experience in a customer-facing technical role (Technical Support, Solutions Engineering, or Software Engineering) at a cloud or SaaS provider.
• SQL proficiency — strong grasp of JOINs, Partitions, Window Functions, Aggregations, CTEs, and sub-queries.
• SQL query performance troubleshooting and query plan analysis.
• Proficient in data modeling concepts.
• Ability to chart data into logical visualizations.
• A proven track record of building trust with customers and bringing issues to resolution quickly.
• Excellent verbal and written communication skills.
• A strong desire to build scalable processes for issue resolution — documenting common patterns and building tooling for diagnosing issues.
• Strong collaboration skills and the ability to work with multiple departments to coordinate issue triaging, diagnosis, and resolution.

Highly Desirable Skills & Experience

• Supporting a cloud service in production.
• Experience working with Snowflake, Redshift, or BigQuery.
• Knowledge of GCP or AWS.
• Startup experience.

Additional Job details

The base salary range for this position is $90k - $125k annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for an annual bonus, stock options, as well as a comprehensive benefits package.

If you do not feel that you satisfy all the listed requirements, we encourage you to still apply. We are enthusiastically looking for people that will help us grow our company and sometimes we are imperfect communicators and can’t articulate perfectly what experience is required for a role. We are looking for people that are excited to grow and constantly ask how we can do things better. If you are excited about the opportunity, we encourage you to apply even if you don’t satisfy 100% of the job requirements.

What You’ll Do: 

DeepIntent is building the intelligence layer of healthcare advertising. This layer runs on well-structured, well-defined, and human- and machine-readable knowledge. As the company accelerates the deployment of internal and external agentic applications, the quality of our underlying data ontology determines how far and how accurate our applications can be. 

Ontology is a new and critical function at DeepIntent, and its core purpose is to organize and curate business context and data across the company. You will build it. Your job is to define, document, and govern how DeepIntent understands its own data. You will be creating and implementing the semantic foundation that enables our people and AI agents to reason with veracity across our business and platform.

Data ontology and knowledge architecture

• Design and maintain DeepIntent's healthcare advertising ontology across healthcare and media domains
• Map external standards (i.e. ICD-10, etc) to DeepIntent's internal data model, when applicable 
• Build and manage a knowledge graph that connects our data and products into a coherent, traversable semantic layer

Data documentation and discoverability

• Create and own the company data dictionary/spine, making it the authoritative source of truth for every data asset, metric definition, and field
• Ensure all datasets are tagged, described, and discoverable by both humans and AI systems
• Partner with Engineering to embed documentation into data pipelines (dbt, BigQuery, etc.) so it stays current

AI readiness

• Structure data assets so they can be consumed by people as well as LLMs and AI agents with minimal prompt engineering overhead
• Define the schemas, metadata standards, and retrieval patterns that let AI agents reliably query DeepIntent data
• Work directly with Business Intelligence, Revenue Strategy, the Company’s CTO, CEO and AI engineering leads on context architecture for knowledge-dependent workflows.

Governance and alignment

• Partner with teams to help establish and enforce data definitions across functions while resolving definitional conflicts when encountered.
• Participate in a lightweight data governance council across Revenue, Product, Engineering, and Data Science
• Serve as the internal expert on healthcare and media data standards and their application to advertising use cases

Who You Are: 

• 7+ years in data roles with significant focus on data modeling, knowledge management, or semantic architecture
• Experience building or contributing to a knowledge graph, data catalog, or enterprise ontology 
• Strong SQL and data modeling skills; comfort in a cloud data warehouse environment 
• Ability to drive cross-functional alignment on abstract, contested topics — equal parts technical and organizational
• Experience designing data schemas or metadata layers specifically for LLM or AI agent consumption
• Background in health informatics, clinical data, or life sciences — not just healthcare advertising
• Familiarity with MCP (Model Context Protocol) or API schema design for AI tool use
• Familiarity with healthcare and/or media data specifications and standards: ICD-10 codes, claims data, OpenRTB, etc. and how these data can be leveraged

DeepIntent is proud to offer a competitive compensation package inclusive of a base salary range of $180,000- $200,000. The base salary range takes into consideration each candidate's skills, experience and qualifications. In addition, we offer an annualized bonus plan and competitive benefits as well as many other company offerings.