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.

IMC Americas, Inc. has multiple openings for Trader (REQ#4461664101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Develop, maintain, and enhance mathematical models, strategies, and trading system components for quantitative proprietary trading in collaboration with developers (10%).
• Independently design and implement changes to trading models, strategies, and systems from end-to-end, including conceiving of proposed changes, creating a testing plan, and performing tests, and implementing changes (15%).
• Analyze, interpret, and model financial, economic, and industry data to optimize trading and maximize revenue generation using existing internal tools (15%).
• Create custom analysis tools for use at the firm to perform research beyond available analysis tools (5%).
• Prepare and present high-quality financial analysis and reports following IMC global guidelines (15%).
• Perform daily operational tasks on the trading desk, ensuring systems are running correctly and escalating as needed to designated contacts (15%).
• Supervise and mentor graduate traders and interns (10%).
• Train graduate traders through the firm's traineeship (5%).
• Contributing to planning and prioritization decisions of future projects on their trading desk (5%).
• Monitoring and managing a trading firm's risk exposure (5%).

Partial telecommuting permitted. Multiple positions available. Requisition Number: 4461664101

Your Skills and Experience

This position requires a Bachelor's degree, or foreign equivalent, in Mathematics, Econometrics, Computer Science, Financial Engineering, Physics, or similarly quantitative and mathematical field and one (1) year of experience in the job offered or a related position.

Must have experience in the following skills:

• Developing, maintaining, and enhancing mathematical models, strategies, and trading system components for quantitative proprietary trading in collaboration with developers;
• Operating trading strategies through a range of market circumstances, having a thorough understanding of risk at any point in time;
• Rolling out and verifying new features on trading strategies;
• Managing a trading firm's risk exposure;
• Using Python and python coding libraries, including Pandas, NumPy, and SciPy to assist in quantitative analysis; and
• Experience trading products and navigating compliance regulations in trading markets. 

Requires FINRA Certifications: (1) SIE and (2) Series 57.

#LI-DNI

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank is seeking a VP-level Applied AI & Machine Learning Scientist to design, build, and validate production-grade AI/ML and Generative AI solutions in a highly regulated banking environment. This role focuses on high-impact use cases—fraud detection, AML alert optimization, AI-assisted credit memo generation for underwriting decision support, contact center AI assistant/copilots, and personalization for treasury/commercial clients—delivered with rigorous governance, explainability, fairness testing, privacy-by-design, cybersecurity, and model lifecycle controls aligned to SR 11-7 and MCB’s Trustworthy & Responsible AI Principles. The role emphasizes Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Applied AI/ML development:

• Design and implement models for fraud detection, AML alert scoring/triage, AI-generated credit memo drafting and underwriting decision support, contact center AI assistants, and personalization for commercial/treasury use cases.
• Leverage modern methods: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings and vector databases, transformers, boosting, anomaly/outlier detection, and classical ML.
• Embed explainability (e.g., SHAP, interpretable scorecards/monotonic models) and conduct pre-/post-deployment bias testing with documented remediation.

Model validation, documentation & governance (SR 11‑7):

• Produce audit-ready documentation (methodology, assumptions, data lineage, limitations, testing) and register models in the inventory with owners/materiality.
• Facilitate independent validation/effective challenge; obtain required approvals before deployment; maintain change management and periodic review cadence.
• Define monitoring, drift thresholds, retraining triggers, and safe rollback/kill-switch procedures; maintain human-in-the-loop checkpoints for high-impact decisions.

Productionization & MLOps on Snowflake

• Package, deploy, and operate models via CI/CD, containerization, and model registry; instrument KPIs/KRIs and alerting dashboards. Operate models natively on Snowflake using Snowpark Python, UDFs/UDTFs, Tasks/Streams, and secure external access where required.
• Partner with Engineering to integrate models via secure APIs/batch; ensure scalability, resiliency, and observability in cloud/on‑prem (e.g., Snowflake, Azure ML, Databricks).

Regulatory, privacy, and cybersecurity alignment:

• Design for ECOA/Reg B (adverse action specificity), UDAAP, FCRA, GLBA privacy, and NYDFS 23 NYCRR 500 cybersecurity requirements.
• Apply privacy-by-design (data minimization, purpose limitation, retention), strong access controls/segregation, and secure SDLC/red teaming for GenAI stacks.

Third‑party AI & data stewardship:

• Support due diligence, testing, and ongoing monitoring of vendor AI/data providers per SR 23‑4; evaluate conceptual soundness, fairness, and security.
• Negotiate/verify contractual controls (no vendor training on MCB/NPI, subprocessors disclosure, audit rights, exit/portability).
• Ensure AEDT compliance (NYC Local Law 144) for any HR-related AI tools.

Cross‑functional partnership:

• Collaborate with Model Risk, Compliance/Legal, Cyber/IT, Data Privacy, Internal Audit, and business owners to meet objectives while staying within risk appetite.
• Communicate complex results, risks, and limitations clearly to technical and non‑technical stakeholders (management committees, examiners).

Innovation, coaching, and best practices:

• Evaluate emerging ML/GenAI methods, LLM evaluation techniques, Snowflake‑native capabilities (e.g., vector search, orchestration), and governance tooling; lead POCs within established control gates.
• Mentor junior staff; promote responsible AI practices, documentation standards, and reproducibility.

Qualifications & Skills:

• 6+ years of relevant work experience.
• Expertise in Python (pandas, scikit‑learn), deep learning (PyTorch/TensorFlow), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• MLOps proficiency with CI/CD, containerization (Docker), registries, and observability; cloud ML (Snowflakes-native ML, Azure ML or Databricks preferred).
• Snowflake‑native ML proficiency: Snowpark Python, UDFs/UDTFs, Tasks/Streams; ability to build and operate ML workflows inside Snowflake.
• Data engineering competency (SQL, ETL/pipelines, Spark/PySpark); ability to work with structured/unstructured data.
• Explainability (e.g., SHAP) and fairness testing; ability to produce interpretable reason codes for ECOA/Reg B adverse actions as applicable.
• Strong grasp of SR 11‑7 lifecycle, model documentation, and operational monitoring within three lines of defense governance.
• Excellent communication; ability to translate technical detail to business/risk stakeholders and drive decisions.
• Curiosity and problem‑solving mindset; ability to balance innovation with disciplined risk management.

Preferred Qualifications & Skills

• Master’s or PhD in a relevant field (Computer Science, Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML, NLP, or model interpretability.
• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions; experience with feature management/registry tooling a plus. model registry and pipeline orchestration; Kubernetes a plus.
• RAG architectures, vector databases, prompt engineering, and LLM evaluation (accuracy, hallucination, safety).
• Fairness toolkits and XAI frameworks; experience preparing models for validation, audit, or regulatory exam discussions.
• Familiarity with SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment
• Must have excellent written and verbal communication skills
• Must be a good listener and good teacher
• Demonstrate analytical, troubleshooting and problem-solving skills
• The ability to learn new technologies quickly
• Self-directed individual with technology and communication skills.
• Ability to take in multiple sources of information with an understanding of the bigger picture need, want, and operation of the Bank.
• Collaborative team-player who can find creative and practical solutions in a dynamic work environment.
• Ability to handle ambiguity, juggle multiple matters at once, and quickly and seamlessly shift from one situation or task to another.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions 
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
• Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As a Senior Value Engineering Consultant specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As an Senior Value Engineer specializing in CPG and Fleet Logistics, you are pushing the envelope in solving business-critical problems for some of the world's most recognized consumer brands and global mobility networks. You will be working intimately with our most strategic enterprise clients, understanding their uniquely complex objectives—spanning from high-velocity beverage manufacturing and Direct Store Delivery (DSD) optimization to massive-scale fleet lifecycle management and dynamic asset routing. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers' massive supply chains, vehicle fleets, and distribution networks. This enables them to industrialize AI, unlocking real ROI on deployments at scale—ensuring products are always on the shelf and vehicles are always ready for the customer. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Chief Supply Chain Officers (CSCOs) and Fleet Operations Executives, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis across these premier global networks.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct supply chain challenges inherent to high-volume CPG and fleet mobility (e.g., predictive demand forecasting, route optimization, fleet predictive maintenance, dynamic asset allocation, and mitigating raw material volatility). As a Celonis product and logistics domain expert, translate these complex, physical-world challenges into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle within various manufacturing, distribution, and fleet management business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and telematics networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, and DSD execution.

• Agentic Process Transformation: Support these enterprise clients in achieving tangible ROI from AI at scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous fleet rebalancing, intelligent shipment exception handling, or automated trade promotion deductions).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs (e.g., SAP), Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and massive IoT/telematics data streams.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for CPG and Mobility Supply Chains, scaling knowledge across the organization regarding the nuances of fast-moving consumer goods and asset-heavy fleet operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, CPG/Beverage, or Fleet Logistics environments. This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume manufacturing and mobility (such as Direct Store Delivery (DSD), Order-to-Cash, Procure-to-Pay, Fleet Lifecycle Management, or Sales & Operations Planning) with the ability to translate high-level operational needs into specific AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent dispatch assistants, or automated extraction of data from complex vendor contracts and logistics documentation).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional and IoT datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, logistics directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for enterprise-grade supply chain environments.

• Familiarity with CPG and fleet-specific systems (e.g., SAP APO/IBP, Blue Yonder, Manhattan, or major telematics/fleet tracking platforms).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Your Impact on our Mission

Zocdoc’s most important asset is our people. As a Staff Data Scientist, Marketplace, you’ll play a meaningful role in transforming healthcare by shaping how millions of patients discover and book care.

The Marketplace team is responsible for driving patient demand, optimizing the search and booking experience, and ensuring a healthy, high-performing two-sided marketplace. This includes areas such as Growth, Search, Insurance, and Patient Home.

As a strategic technical leader on the Marketplace Analytics team, you’ll design and scale analytical frameworks that inform product and growth strategy, guide experimentation, and optimize performance across the patient funnel—from acquisition through booking and retention. Your work will directly improve marketplace liquidity, efficiency, and long-term value.

You’ll enjoy this role if you are…

• Passionate about transforming healthcare through data and turning complex datasets into meaningful product insights

• A force multiplier who loves mentoring and enabling teams to deliver scalable, high-impact work

• Comfortable operating at the intersection of business strategy, data science, and product innovation

• Energized by complex, ambiguous problems and skilled at translating them into structured analytical solutions

• Personally motivated by building systems, frameworks, and capabilities that outlast any one analysis

• Serious about your work, but not about yourself — you value rigor and humility equally

Your day to day is…

• Partnering with Product, Marketing, Finance, Engineering, and Commercial teams to translate insights into actionable product and business strategy

• Architecting and executing experimentation frameworks, including A/B testing design, power analysis, variance reduction, and advanced causal inference methodologies (e.g., DiD, synthetic controls, propensity modeling, causal forests)

• Identifying, designing, and guiding the development of analytical models (e.g., LTV, survival, uplift models) to improve provider utilization, acquisition, retention, patient engagement, and client ROI

• Establishing scalable statistical frameworks and best practices to quantify the impact of product and commercial initiatives

• Partnering with Engineering to ensure data quality, event instrumentation, feature availability, and scalable pipelines that enable trustworthy analysis

• Mentoring and upskilling analysts and data scientists, raising the bar for analytical rigor and impact across Zocdoc

• Advancing AI-assisted analytical workflows to streamline recurring analysis and decision support

• Working with cutting edge GenAI tools and technology

You’ll be successful in this role if you have…

• An unrelenting desire to build more equitable, inclusive, and diverse workplaces, and view this role as an opportunity to create positive change

• 8+ years of experience in data science, machine learning, or related quantitative roles

• Proven success developing LTV models, survival models, uplift models, or similar predictive frameworks for customer targeting and optimization

• Deep expertise in SQL and Python (pandas, NumPy, scikit-learn, statsmodels)

• Strong knowledge of experimentation and causal inference, including statistical power analysis, experiment design, and quasi-experimental methodologies

• Experience shaping and scaling analytics functions—not just building individual models

• Experience working in cross-functional product organizations

• The ability to integrate generative AI tools into daily workflows to automate tasks, foster innovation, and maximize productivity

• Superb communication skills and the ability to influence non-technical stakeholders

• The mentality of an entrepreneur/owner with a strong bias to action

• Humility — you treat all people with dignity and respect, regardless of title or tenure

Nice to have

• Master’s or PhD in Statistics, Economics, Applied Math, or another quantitative field

• Experience within a SaaS organization

Benefits

• Flexible, hybrid work environment at our convenient Soho location

• Unlimited Vacation

• 100% paid employee health benefit options (including medical, dental, and vision)

• Commuter Benefits

• 401(k) with employer funded match

• Corporate wellness program with Wellhub

• Sabbatical leave (for employees with 5+ years of service)

• Competitive paid parental leave and fertility/family planning reimbursement

• Cell phone reimbursement

• Catered lunch everyday along with beverages and snacks

• Employee Resource Groups and ZocClubs to promote shared community and belonging

• Great Place to Work Certified

Role Description

• As an Applied AI Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 7+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

The Role

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. As a Quantitative Researcher, you’ll operate near the tip of the spear in a collaborative, dynamic environment. This includes close partnership with other researchers, traders, and engineers on quantitative problem-solving, trading strategy generation, back-testing, statistical analysis, and system design. Our environment of collaborative innovation and intellectual curiosity allows us to share in our victories while continually challenging ourselves to stretch the limits of our creativity. Take advantage of this opportunity to apply the scientific method to business problems as part of one of our Quant teams at CTC! 

We prioritize team matching at the outset of our hiring process, thoughtfully considering which of our two teams (Vol Overlay or Delta Force) offers the best fit for each candidate’s strengths and interests while also aligning to the firm’s highest priority needs. 

What We’re Looking For   

We are seeking a Quantitative Researcher who can seamlessly blend academic rigor with practical application in our fast-paced trading environment. This individual will partner with our Trading and Technology teams to strengthen, scale, and evolve the firm's trading capabilities. The ideal candidate will possess a unique combination of analytical prowess, programming skills, and eye for business, driving innovation and results in quantitative finance. 

Responsibilities 

• Analyze market data to come up with economic and microstructure hypotheses 
• Build predictive and explanatory models to describe financial markets 
• Add revenue by applying thorough research processes to real life business problems 
• Contribute to ongoing improvement of research and trading infrastructure 

Qualifications 

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Applied Mathematics, or Operations Research) 
• Proven ability to conduct independent, high-quality research 
• Exceptional ability to communicate complex ideas and research results, both in writing and verbally 
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes. 
• Demonstrated expertise in applying quantitative modeling techniques to large, complex datasets 
• Strong track record of publications in an industry setting 
• Advanced Python programming skills 

Nice to Have 

• Proficiency in C++ 
• Experience in financial markets 
• Experience using NumPy and Pandas libraries 
• Experience with the software development lifecycle 

About the Role

We’re looking for a Director of Engineering to lead our Intelligent Messaging group—one of the most critical and high-impact areas at Attentive. This team powers the systems behind billions of personalized messages (SMS, email, push) sent every month, helping the world’s leading brands connect with consumers in smarter, more meaningful ways.

At the core of this is AI, machine learning, and real-time data. This allows us to drive personalization at massive scale - turning every message into an opportunity to engage, convert, and build long-term customer relationships.

In this role, you’ll lead multiple teams and play a key role in defining how AI shapes the future of messaging at Attentive. You’ll partner closely with Product and Engineering leadership to build and scale systems that are fast, reliable, and deeply intelligent. You’ll stay close to the work - guiding architecture, unblocking complex problems, and stepping in when it matters - while also building strong teams and developing great managers.

This is a role for someone who likes to operate deep in the systems, close to the people, and aligned with the business. You’ll own the technical direction of a high-scale, high-uptime platform and help us push what’s possible as we continue to grow.

This is a hybrid role based in NYC, with occasional travel to our SF office.

What You’ll Accomplish

• You’ll own the delivery of cutting-edge, AI-powered consumer messaging experiences used by millions
• You’ll manage and evolve a multi-team organization, build on our great culture, and set a high bar for engineering excellence
• You'll oversee the technical strategy in multiple domains, supporting various layers of our messaging applications by using existing and emerging technology platforms
• You’ll accelerate our engineering velocity using cutting-edge agentic and LLM tooling, while successfully managing safety and stability
• You’lll collaborate with product, ML, design, and data science to shape the roadmap - not just execute on it
• You’ll work directly with partner teams and stakeholders in the platform, go-to-market, and customer success organizations

Your Expertise

• Above all else, you are technical and love to dive deep to understand architecture, code, and infrastructure. This is the most critical attribute for success at Attentive.
• You have 10+ years of industry experience, including managing teams of 30+ engineers, and at least 2 years managing managers. From a technical perspective, you have 8+ years of experience in software engineering roles, ideally reaching staff level as an individual contributor.
• You embrace agentic workflows, and understand the benefits, complexity and risks of the fast-moving AI ecosystem
• You care about software quality and have a track record of building reliable, high-uptime systems, particularly in data-intensive environments
• You’re comfortable operating in fast-moving, high growth environments, translating business needs into the right levels of implementation

What We Use

• Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS
• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $250,000 - $350,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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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.

For The Points Guy website click here. Curious how The Points Guy fits into Red Ventures? Click here.

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!

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#BR

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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By applying for this position, your data will be processed as per Attentive's Privacy Policy.

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!

About the role:

We are seeking an exceptional Applied Scientist to work on core search systems that power our product, with a particular focus on provider selection and recommendation algorithms. You will play a pivotal role in shaping how Garner selects high-value providers for members by developing the evaluation frameworks, objective functions, and algorithms that drive our search experience.

This role is ideal for someone who is excited by ambiguous, high-impact problems and can translate messy real-world constraints into robust algorithmic systems. You will partner closely with Product and Engineering to design and deliver production algorithms that balance provider quality, affordability, and access.

Where you will work:

This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. 

What you will do:

• Build and own the algorithms that power Garner’s search
• Design objective functions, scoring frameworks, and decision logic that balance competing goals such as quality, cost, and access
• Translate ambiguous product and business problems into rigorous algorithmic approaches that can be deployed in production
• Partner with engineers to productionize systems at scale
• Identify where applied machine learning, optimization, heuristics, or rules-based methods are the right tool for a problem
• Develop a strong understanding of the healthcare economy

The ideal candidate has:

• 4+ years of experience using Python and SQL to build production, data-driven algorithms
• Strong applied problem-solving skills, with the ability to define good metrics and design algorithms under ambiguity
• Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem
• Strong communication skills and the ability to synthesize complex algorithmic ideas for business and technical stakeholders
• A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Python, SQL, AWS, Snowflake, pandas, XGBoost

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time.

Compensation Transparency:

The target salary range for this position is $200,000 - $240,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more.

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed!

Responsibilities 

• Analyze time series network and exchange protocol captures
• Become familiar with the details of specific markets, attend presentations and liaise with exchange counterparts
• Research exchange features, capabilities, and architecture
• Automate collection and visualization of metrics that quantify efficacy of exchange communication
• Formulate and conduct controlled experiments that measure impact of calculated changes to HRT’s trading infrastructure
• Communicate ideas, requirements, and results across disparate teams
• Improve fill rate of our hardware-based trading strategy
• Reduce incidence of cancel-reject responses
• Investigate and report details of various latency-sensitive exchanges

Profile 

• You possess a degree in Data Analytics or a related field
• You can collect and interpret network and/or financial market data
• You have professional experience in latency reduction, preferably in finance
• You have a basic understanding of proprietary trading and exchange technologies

Skills 

• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Basic understanding of TCP and UDP network protocols
• Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy)
• Some familiarity with the details of modern computer systems and networks
• Experience with real time exchange market data and order entry a plus

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development team. Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models. 

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.

Profile

• You’re excited to apply your research expertise to identify new opportunities in worldwide markets  
• You enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently
• You are a critical thinker who can learn and implement new skills in a fast-changing environment

Qualifications

• You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2026
• Fluency in Python
• Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
• Brilliant analytical and problem-solving skills
• Ability to work creatively and independently on long-term technical problems

The estimated base salary for this position is 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed! 

Responsibilities

• Contribute directly to impactful improvements to HRT’s low-latency trading systems
• Analyze large datasets to understand how complex systems and networks behave in real-world conditions, such as exchange technology and performance of HRT systems
• Build Python-based tools and scripts to collect, clean, and visualize data in a clear and actionable way
• Design and run experiments to measure the impact of changes and identify opportunities for improvement
• Collaborate closely with HRT’s Algorithm Development, Trading Technology, and Business Development teams to discover, research, and implement improvements to HRT’s architecture
• Liaise with exchanges globally to better understand their technology and stay up to date on changes and improvements

Qualifications

• A technical degree or equivalent practical experience
• Experience with Python and Pandas 
• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Strong curiosity about how financial systems, networks, and cutting-edge technology work, and a willingness to learn new concepts quickly
• Ability to think analytically, ask insightful questions, and approach unfamiliar problems methodically
• Strong cross-functional communication skills and an interest in collaborating with others

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological innovation. We build and deploy cutting-edge systems within one of the world’s most advanced computing environments to power our global trading operations. Our non-siloed, collaborative coding environment empowers talented engineers to make significant contributions and see their impact daily. At HRT, you'll be challenged to solve the most complex problems in trading alongside many of the brightest minds in the field.

We are seeking highly motivated and skilled Research Engineers who will work very closely with our Algo Developer (Quant Research) trading teams. These roles require exceptional programming fundamentals, a strong user focus, and the ability to thrive in a fast-paced environment with constantly evolving requirements. Multitasking and context switching are inherent aspects of this role, through which you will gain insight into the ideation and execution of some of the world's most sophisticated trading strategies.  

Research Engineers at HRT work on a wide variety of projects. Examples include:

• Designing highly customized quantitative systems that enable Algo Developers to easily express and backtest new predictive signals.
• Building world-class research tooling to speed up Algo Developers’ research iteration.
• Aiding the development and deployment of very large deep learning models for HRT’s live trading.
• Improving HRT’s monetization systems which turn our predictions into profitable trades.
• Evaluating sim vs. live differences to improve the fidelity of our simulations.
• Building systems to monitor and manage live trading.
• Specializing in specific time horizons, from high frequency trading to mid-to-low frequency hedge fund-style strategies.
• Working across a very wide variety of asset classes (from equities to fixed income to options) and regions (from North America to Asia Pacific) – you’ll interact with markets across the world!

Responsibilities

• Design, develop, and maintain robust, performant, and scalable software systems.
• Optimize existing codebases for performance, reliability, and efficiency.
• Debug complex issues across distributed systems in a time-sensitive environment.
• Optimize both the mechanics and ergonomics of Algo Developer research workflows; this requires developing a deep intuition for research methodologies.
• Balance the short term goals of individual trading teams with the longer term goals of HRT’s generalized trading platforms across trading teams. Because we don’t work in a pod environment, REs on different trading teams are expected to share technology and ideas.

Qualifications

• Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
• Previous experience at a top-tier finance or technology company with an excellent track record of rapid advancement and superlative reviews.
• Experience with supporting internal users is preferred; bonus if you have real hands-on experience with quant research and/or ML/Deep Learning platforms.
• Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.)
• Candidates should be prepared for technical interviews in either Python or C++. While there is no hard language requirement for RE roles, proficiency in one of these languages will be assessed during the interview process.
• Kindness and empathy is a real requirement. No “smart jerks” at HRT. 
• Strong understanding of data structures, algorithms, and design principles.
• Excellent communication skills, both written and verbal.
• HRT ships every day. The ability to thoughtfully, methodically, and reliably deploy new software and features is a critical skill. 
• If you have management experience, that’s always a bonus – but even so, expect to code!

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

For more info about interviewing at HRT, see this blog!

About the Role

Charlie Health leads the nation in high-acuity virtual behavioral care, having delivered life-saving treatment to more than 100,000 clients nationwide. Our Matching and Outcomes team builds products to measure and improve clinical outcomes, including provider recommendation systems for clients and clinical decision support tools, enabling durable and effective treatment. You'll create predictive models and workflows to match patients with the best-fit therapists and peers, and enable clinicians to tailor care to each client's individual needs. The systems you build will help clinicians condense and synthesize knowledge across our clients and providers into actionable guidance at every moment. If you care about using data-driven insights to improve outcomes, this team is for you.

Responsibilities

• Design, train, and evaluate machine learning models and AI systems that drive meaningful business impact
• Identify opportunities to introduce or improve data-driven algorithms and automated solutions in partnership with clinical, design, data science, and product teams
• Pioneer new approaches to measure and validate outcomes impact through advanced experimentation and causal inference techniques
• Utilize ML infrastructure to serve model inferences in real time using live data streams
• Write production code within a backend Python monolith to invoke ML predictions.
• Foster a culture of collaboration and learning across engineering, product, and design through mentoring, documentation, presentations, and knowledge sharing

Requirements

• A bachelor’s degree in a technical field, plus 4+ years of professional experience developing and delivering production software, including machine learning models; OR
• A master’s or doctorate degree in a technical field, plus 2+ years of professional experience developing and delivering production software, including machine learning models.
• Expertise in Python for ML (pandas, sklearn, etc.) and backend server development (FastAPI)
• Strong SQL skills and experience navigating analytical and transactional databases to assess and curate high-quality datasets
• Experience developing agentic AI workflows is a plus
• Excellent at managing ambiguity—able to break down big, messy problems into smaller parts with tractable solutions and clear iterations
• Growth mindset and sense of humor; you welcome feedback, adapt quickly in a fast-paced environment, and foster a culture of learning and fun
• This role requires 4 days per week in our NYC office (Flatiron District). The team is entirely based out of NYC.

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

The total target base compensation for this role will be between $170,000-$220,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits.

About the Role

The Revenue Engine team at Charlie Health services all parts of our business related to revenue collection, financial reporting, and the patient financial experience by sourcing, curating, and activating internally and externally sourced datasets, and building user-facing products. As a data engineer on the Revenue Engine team, you will be responsible for building ELT pipelines, developing custom DAGs, transforming and warehousing data with DBT, and building integrations between our systems.

We’re a team of passionate, forward-thinking professionals eager to take on the challenge of the mental health crisis and play a formative role in providing life-saving solutions. If you’re inspired by our mission and energized by the opportunity to increase access to mental healthcare and impact millions of lives in a profound way, apply today.

Responsibilities

• Develop, release, and maintain high quality data pipelines using Python, FiveTran, DBT, and Snowflake.
• Own and guide the development of our data infrastructure.
• Orchestrate complex data workflows using Dagster.
• Identify bottlenecks and implement improvements to our data engineering processes, tools, and procedures. Everyone on our team shares responsibility for continuously improving how we work.
• Promote a culture of collaboration and learning across the technology team via mentoring, documentation, presentations, or other knowledge-sharing methods.
• Ensure our data is always available by participating in our on-call rotation.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, or other technical discipline, or equivalent practical experience
• 7+ years experience in engineering, with at least 5 years of experience in a data engineering role
• Deep expertise in SQL. You understand CTEs, aggregation functions, window functions, partitioning and clustering approaches to run correct and highly-performant queries
• High proficiency in Python and experience using common data engineering libraries such as Pandas, Numpy, and Great Expectations
• Experience with a modern data stack. Experience with our tools - FiveTran, Snowflake, DBT, Dagster, and Tableau - is a big plus
• Experience with data exploration, profiling, governance, visualization, and activation
• Proven ability to thrive in an ambiguous and rapidly changing environment
• Experience working with sensitive data in a regulated environment
• Expertise in healthcare and/or revenue cycle management is a plus
• You live within a 75 minute commute of our NYC office (near Union Square) and are able to work in-office 4 days per week. 

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

The total target base compensation for this role will be between $175,000 and $255,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. #LI-HYBRID

About the Role

The Revenue Engine team at Charlie Health services all parts of our business related to revenue collection, financial reporting, and the patient financial experience by sourcing, curating, and activating internally and externally sourced datasets, and building user-facing products. As a data engineer on the Revenue Engine team, you will be responsible for building ELT pipelines, developing custom DAGs, transforming and warehousing data with DBT, and building integrations between our systems.

We’re a team of passionate, forward-thinking professionals eager to take on the challenge of the mental health crisis and play a formative role in providing life-saving solutions. If you’re inspired by our mission and energized by the opportunity to increase access to mental healthcare and impact millions of lives in a profound way, apply today.

Responsibilities

• Develop, release, and maintain high quality data pipelines using Python, FiveTran, DBT, and Snowflake.
• Own and guide the development of our data infrastructure.
• Orchestrate complex data workflows using Dagster.
• Identify bottlenecks and implement improvements to our data engineering processes, tools, and procedures. Everyone on our team shares responsibility for continuously improving how we work.
• Promote a culture of collaboration and learning across the technology team via mentoring, documentation, presentations, or other knowledge-sharing methods.
• Ensure our data is always available by participating in our on-call rotation.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, or other technical discipline, or equivalent practical experience
• 7+ years experience in engineering, with at least 5 years of experience in a data engineering role
• Deep expertise in SQL. You understand CTEs, aggregation functions, window functions, partitioning and clustering approaches to run correct and highly-performant queries
• High proficiency in Python and experience using common data engineering libraries such as Pandas, Numpy, and Great Expectations
• Experience with a modern data stack. Experience with our tools - FiveTran, Snowflake, DBT, Dagster, and Tableau - is a big plus
• Experience with data exploration, profiling, governance, visualization, and activation
• Proven ability to thrive in an ambiguous and rapidly changing environment
• Experience working with sensitive data in a regulated environment
• Expertise in healthcare and/or revenue cycle management is a plus
• You live within a 75 minute commute of our NYC office (near Union Square) and are able to work in-office 4 days per week. 

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

The total target base compensation for this role will be between $175,000 and $255,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. #LI-HYBRID

About the Role

Charlie Health leads the nation in high-acuity virtual behavioral care, having delivered life-saving treatment to more than 100,000 clients nationwide. Our Matching and Outcomes team builds products to measure and improve clinical outcomes, including provider recommendation systems for clients and clinical decision support tools, enabling durable and effective treatment. You'll create predictive models and workflows to match patients with the best-fit therapists and peers, and enable clinicians to tailor care to each client's individual needs. The systems you build will help clinicians condense and synthesize knowledge across our clients and providers into actionable guidance at every moment. If you care about using data-driven insights to improve outcomes, this team is for you.

Responsibilities

• Design, train, and evaluate machine learning models and AI systems that drive meaningful business impact
• Identify opportunities to introduce or improve data-driven algorithms and automated solutions in partnership with clinical, design, data science, and product teams
• Pioneer new approaches to measure and validate outcomes impact through advanced experimentation and causal inference techniques
• Utilize ML infrastructure to serve model inferences in real time using live data streams
• Write production code within a backend Python monolith to invoke ML predictions.
• Foster a culture of collaboration and learning across engineering, product, and design through mentoring, documentation, presentations, and knowledge sharing

Requirements

• A bachelor’s degree in a technical field, plus 4+ years of professional experience developing and delivering production software, including machine learning models; OR
• A master’s or doctorate degree in a technical field, plus 2+ years of professional experience developing and delivering production software, including machine learning models.
• Expertise in Python for ML (pandas, sklearn, etc.) and backend server development (FastAPI)
• Strong SQL skills and experience navigating analytical and transactional databases to assess and curate high-quality datasets
• Experience developing agentic AI workflows is a plus
• Excellent at managing ambiguity—able to break down big, messy problems into smaller parts with tractable solutions and clear iterations
• Growth mindset and sense of humor; you welcome feedback, adapt quickly in a fast-paced environment, and foster a culture of learning and fun
• This role requires 4 days per week in our NYC office (Flatiron District). The team is entirely based out of NYC.

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

The total target base compensation for this role will be between $170,000-$220,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits.

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This position is based in our Tempe, Arizona office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This is a remote position, open to candidates who reside in: Dallas, Texas. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area. #LI-Remote

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $101,844 - $133,670 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This is a remote position, open to candidates who reside in: Atlanta, Georgia. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area. #LI-Remote

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

DRW is a major Chicago-based proprietary trading firm founded in 1992 by Don Wilson, specializing in diversified, technology-driven market-making and quantitative trading across asset classes including fixed income, options, derivatives, commodities, energy, equities, FX, and cryptocurrency.

DRW is building out a dedicated prediction markets desk focused on platforms such as Polymarket and Kalshi. As a Prediction Markets Trader, you will develop, execute, and optimize high-conviction trading strategies in binary event contracts. You will manage a live portfolio, targeting consistent positive expectancy through market making, microstructure exploitation, cross-platform arbitrage, event-driven momentum, and statistical models. This role requires genuine, demonstrated passion for prediction markets, strong quantitative reasoning, and the ability to operate in thin, volatile, event-resolution-driven environments.

Core Responsibilities:

• Monitor and trade active markets in real time across Polymarket (CLOB/Gamma/Subgraph APIs) and Kalshi (FIX/WebSocket/REST).
• Execute strategies including: market making with dynamic skew, microstructure arbitrage (order-flow and book-imbalance sniping), cross-platform arb, news/event momentum (sub-second reaction), and statistical pairs/mean-reversion.
• Develop and backtest models using historical tick data, Bayesian probability updates, NLP sentiment parsing, and ML for fair-value estimation.
• Collaborate with engineering on low-latency infrastructure (API integrations, order engines, anomaly detection).

Required Qualifications:

• Bachelor's or higher in Quantitative Finance, Statistics, Computer Science, Economics, Mathematics, or equivalent.
• Strong programming skills: Python (pandas, NumPy, backtesting).
• Solid foundation in probability, statistics, time-series analysis, and Bayesian methods.
• Hands-on experience with prediction market platforms (Polymarket and/or Kalshi APIs) or closely related domains (options, binary events, sports/event betting).
• Genuine, demonstrated interest in prediction markets — we expect you to be actively engaged with the space (personal trading, deep reading of protocols, following major resolutions, contributing to discussions, etc.). This is non-negotiable.

Highly Valued (but not strictly required):

• Prior profitable trading experience in prediction markets, options, or event-driven strategies (personal or professional).
• Familiarity with blockchain/DeFi tools (ethers.js, Polygon RPC, USDC wallets).
• Experience with low-latency systems, FIX protocol, or Web3 integrations.
• Track record of building and backtesting quantitative models with real historical data.
• Deep domain knowledge of high-impact events (politics, macroeconomics, climate, sports).

Who We’re Looking For: We are especially interested in exceptionally sharp, self-motivated individuals — including strong campus hires and new graduates — who are obsessed with prediction markets and can demonstrate clear, substantive engagement with the space. If you’ve been actively trading Polymarket/Kalshi, analyzing resolutions, building personal models, or following the ecosystem closely, we want to talk to you.

Apply With: 

• Resume
• Cover letter explicitly detailing your genuine interest in prediction markets (specific examples of your engagement: trades you’ve made, resolutions you’ve studied, models you’ve built, protocols you follow, etc.)
• GitHub, personal blog, or portfolio links showing relevant work

Applications reviewed on a rolling basis. Strong candidates will receive a technical screen, strategy discussion, and live coding/modeling exercise focused on real prediction market scenarios.

Location:  Flexible.  US-based preferred.

The annual base salary range for this position is $175,000 to $200,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus.  In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

#LI-GV1

Mid-level Applied AI Data Scientist (Tableau Focus)

Location: New York, NY (Hybrid – 3 days in-office) | Practice Area: Technology & Engineering | Type: Permanent

Turn data into insight, and insight into impact.

The Role
We are looking for a Data Scientist to join us, working at the intersection of data, machine learning, and business insight. In this role, you will apply statistical and machine learning techniques to real-world problems, helping clients unlock value from complex datasets. You will collaborate with cross-functional teams and contribute to the development of scalable, data-driven solutions.

What You’ll Do

• Apply statistical analysis, clustering, and probabilistic techniques to generate actionable business insights
• Work with structured and semi-structured datasets to identify patterns, trends, and anomalies
• Build and support NLP workflows, including named entity recognition (NER), entity resolution, and text classification
• Develop machine learning models with guidance from senior team members, contributing to evaluation and refinement
• Create Tableau dashboards and visualizations to communicate insights to technical and non-technical stakeholders

What We’re Looking For

• 3–7 years of experience in data science, analytics, or applied machine learning
• Strong foundation in statistics, probability, and core machine learning techniques (e.g., regression, classification, clustering)
• Hands-on experience with Python and libraries such as pandas, NumPy, and scikit-learn
• Experience building Tableau dashboards to clearly communicate data insights
• Ability to collaborate across teams and translate analytical findings into business-relevant outcomes

Bonus Points For

• Experience working with graph-like or network datasets
• Exposure to ML Ops practices such as experiment tracking, model versioning, and monitoring
• Hands-on experience with NLP techniques such as entity extraction or text processing
• Familiarity with cloud-based data or ML platforms
• Experience contributing to rapid prototyping or iterative AI solution development

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions
• Work in a collaborative, flat, and entrepreneurial consulting culture
• Access continuous learning, training, and industry certifications
• Be part of a team shaping the future of digital financial services
• Help shape the future of digital transformation across FS & Energy.

Use of Artificial Intelligence in Talent Acquisition
At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Benefits

• Medical, Dental, Vision coverage
• 401(k) with employer match
• Maternity and paternity leave, plus dependent care support
• Tuition reimbursement and wellness reimbursement programs
• HSA, FSA, commuter benefits, and employee discount marketplace access

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter.

#LI-MB1

#LI-HYBRID

Project Overview

This is a cutting-edge initiative to integrate Large Language Models (LLMs) with WorldQuant's proprietary strategy management tools. The project aims to provide AI-assisted insights, automate routine analytical tasks, and enable natural language interactions for Portfolio Managers to more efficiently analyze, maintain, and enhance their trading strategies. This involves building foundational infrastructure, developing robust data pipelines for metrics and features, and creating a secure, user-centric interface with a strong focus on protecting intellectual property.

The Role:

We are seeking a talented and motivated Full-Time Software Engineer to play a key role in the development and enhancement of this AI-driven platform. You will be responsible for designing, building, and maintaining critical components of the system, primarily focusing on the Model Context Protocol (MCP) servers that form the backbone of the platform. This includes enhancing existing MCPs, such as our proprietary command-line interface for strategy data, developing new MCPs for internal data system integration, strategy analysis, and performance metrics, and contributing to the secure and effective use of LLMs.

Key Responsibilities

• Design, develop, test, and deploy robust and scalable MCP servers and related tools in Python.
• Enhance existing MCPs, including our internal data access tools, to ensure reliable access to strategy metadata, historical PnL data, and PnL attribution by risk factors.
• Develop new MCPs, including but not limited to MCPs for direct data system integration, MCPs for strategy analytics, and MCPs for performance reporting.
• Design and implement secure prompt engineering techniques to interact with LLMs, ensuring effective information retrieval while minimizing the risk of intellectual property leakage.
• Collaborate with project managers, technical leads, and other developers to define technical specifications and integrate various data sources.
• Work on API development and integration, ensuring seamless data flow between different systems (internal knowledge management systems, simulation systems, data warehouses).
• Implement data parsing and manipulation logic for various formats (JSON, CSV).
• Contribute to the design and implementation of data pipelines for strategy metrics and features.
• Address and resolve bugs and issues in existing MCP tools and infrastructure.
• Participate in code reviews, and contribute to unit and integration testing efforts.
• Create and maintain technical documentation for developed components.
• Stay updated with emerging technologies and methodologies in AI, LLMs, prompt engineering, and financial technology.

What You’ll Bring:

Core Skills:

• Strong proficiency in Python programming.
• Proven experience in API development, integration, and consumption.
• Solid understanding of database interaction, data access patterns, and data modeling.
• Experience with data parsing and manipulation libraries and techniques (e.g., pandas, JSON, CSV).
• Understanding of or experience with prompt engineering principles for Large Language Models
• Awareness of data security and intellectual property protection considerations in the context of AI and LLM applications

Domain-Specific Knowledge (Highly Beneficial):

• Familiarity with financial data (e.g., PnL, Sharpe ratio, alpha, risk factors, AUM).
• Experience with quantitative trading systems, market data systems, or strategy management platforms (familiarity with internal data systems or command-line data tools is a significant plus).

Technical Environment Familiarity (Helpful):

• Experience working in a Linux environment.
• Understanding of Command Line Interface (CLI) tools and development.
• Familiarity with version control systems (e.g., Git).

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong collaboration and communication skills, with the ability to work effectively in a team.
• High attention to detail and commitment to delivering high-quality software.
• Ability to learn quickly and adapt to new technologies and complex systems.

Education

• Bachelor's or Master's degree in Computer Science, Engineering

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

What you’ll do

About the internship

Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

As an intern, you'll tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.

Responsibilities

• Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
• Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
• Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
• Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
• Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.

Who you are

Minimum requirements

• A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
• Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
• Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
• A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
• Intent to return to the degree-program after the completion of the internship/co-op.

Preferred qualifications

You Might Also Have:

• Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
• Published and presented peer-reviewed articles in top-tier venues.
• Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
• Familiarity with navigating new codebases and managing work across different programming languages.
• Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.

Application requirements

Please submit the following with your application:

• A detailed resume or LinkedIn profile showcasing your work history.
• Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.

Join us for an unforgettable summer internship and help shape the future of global commerce. At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.

Polar Operations LLC (dba IMC Markets) has multiple openings for Python Software Engineer (REQ#4461661101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Implement software features and components for IMC's trading systems (25%).
• Design software solutions independently and make architectural decisions (10%).
• Debug and fix software issues in trading systems (5%).
• Identify complex multi-component issues, perform root cause analysis, and implement preventative solutions (5%).
• Ensure code quality and system reliability through comprehensive automated testing (10%).
• Contribute to the automated testing framework, own critical trading system components, and ensure reliability, performance, and scalability across regions (5%).
• Participate in code reviews (10%).
• Monitor system performance and trading operations (5%).
• Collaborate with traders and other teams to understand requirements and deliver solutions (10%).
• Participate in planning, estimate complexity of tasks, and help balance technical debt with feature development (5%).
• Mentor and guide junior developers and interns, helping them understand IMC's systems and development practices (10%).

Partial telecommuting permitted. Multiple positions available. Requisition #: 4461661101

Your Skills and Experience

This position requires a Bachelor’s degree, or foreign equivalent, in Computer science, Computer Engineering, or a similarly quantitative and technical field and one (1) year of experience in the job offered or a related occupation.

Must have at least one (1) year of experience in each of the following skill(s):

• Applying analytical and engineering techniques to solve complex problems programmatically;
• Programming with Python;
• Developing and implementing algorithms and data structures;
• Software development lifecycle and best practices;
• Designing and developing software applications in a collaborative, cross-functional environment;
• Experience with DevOps, databases, big data, or frontend frameworks;
• Experience with Docker, Kubernetes, and Linux environments;
• Experience working with financial data;
• Foundational knowledge of quantitative trading concepts and equity/index options;
• Exposure to web/API frameworks such as FastAPI and React;
• Experience with automated testing and CI/CD pipelines;
• Experience collaborating with trading desks and developing software for use in a quantitative trading environment;
• Experience with the following tools: Team City, JIRA ticket management, Gerrit code review tool, GitLab, uv, Gitlab CI, py-spy, memray, and Python Packaging; and
• Experience with the following libraries: Pandas, Polars, NumPy, Tensorflow, Scikit, scikit-learn, cvxpy, and Pytest.

#LI-DNI

Position Summary

We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this role, you will collaborate closely with data scientists, software engineers, and product teams to translate research models into reliable, scalable, and high-impact applications. You will be deeply involved in the end-to-end ML lifecycle—from data ingestion and feature engineering to deployment, monitoring, and continuous improvement—playing a critical part in shaping our machine learning platform and capabilities.

Primary Responsibilities

• Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications.
• Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments.
• Design and implement data pipelines and workflows that support training, inference, and model lifecycle management.
• Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows.
• Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles.
• Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices.
• Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices.
• Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities.

Qualifications

• Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles.
• Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask).
• Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with CI/CD pipelines, testing automation, and version control using Git.
• Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML) is preferred.
• Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts.
• Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams.

This is an exempt position. The annualized base pay range for this role is expected to be between $140,000-$180,000.  Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed, and the applicant's skill set.  The base pay is just one component of the total compensation package for employees.  Other rewards may include an annual cash bonus and a comprehensive benefits package, including but not limited to medical, dental, vision, life and 401(k). Please note that the job title is subject to change based on the selected candidate’s experience and education.

About the Role 

In this role, you will build and lead our forward-deployed engineering (FDE) team, working directly with leading labs and enterprises to scope, build and deliver high quality datasets to support their most critical AI initiatives. 

You’ll lead a team that will own quality in the end-to-end data pipeline. This will include working with customers to define what “good” data looks like to implement the relevant workflows in their platform. You will design innovative ML approaches to enhance human-in-the-loop (HITL) techniques and improve the efficiency of data generation and review processes. Your team will own systems and tools that enable consistent, scalable, and high-quality data delivery to our customers.

Sitting at the critical intersection of data engineering, ML engineering, operations, and customer engagement— leading scoping and preselling efforts.  You'll also partner closely with the Snorkel delivery team and cross-functional stakeholders to define quality standards, develop measurement frameworks, drive ML-based workflows to improve data pipelines and unblock projects through technical innovation. As the founding member, you’ll also roll up your sleeves to define and own the workflows and processes that are needed to deliver exceptional data at scale.

Main Responsibilities

• Build and lead the Forward Deployed Engineering DaaS organization, setting a clear vision, defining the operating model and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
• Build, mentor, and motivate high performing teams, including cultivating skills and culture needed to consistently deliver exceptional outcomes and transformative impact. 
• Own and evolve the data pipeline components of the DaaS stack, including model-assisted labeling and data generation, quality estimation, and data-centric feedback loops that guide human input
• Partner with customers - including research and engineering teams at Frontier AI Labs - to scope requirements for complex, novel AI datasets and translate needs into delivery-ready workflows 
• Develop robust systems for request intake, task orchestration, SLA tracking, and progress monitoring to ensure seamless execution and prevent critical delivery gaps
• Collaborate cross-functionally with research and engineering teams to innovate, develop, and productionize HITL data generation methods, advanced quality techniques, and improve internal delivery tooling
• Drive continuous improvement by developing reusable workflows, surfacing operational insights, and enabling the organization to scale faster while maintaining high quality

What We’re Looking For

• 10+ years of experience in applied data or ML engineering roles, including 5+ years leading high-performing technical teams in hands-on management capacity
• Demonstrated success in customer facing roles, with a strong enthusiasm for data pipelines and LLM-based workflows.
• Proven track record of managing technical field teams in fast-paced, delivery-focused environments with competing priorities
• Experience as a player-coach—comfortable being hands-on while supporting and scaling the team
• Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
• Strong practical experience with LLM-based workflows, Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
• Bonus: experience working with data annotation workflows or internal tooling for data delivery orgs

Why Join Snorkel AI?

At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to found a function and have a broad, lasting impact across the company.

The Team

Discretionary & Client Solutions Technology is ~35 engineers across London, New York, and Sofia, building the platforms that power Man Group's discretionary investment and client facing operations. We operate at high tempo — shipping multiple production releases weekly across portfolio analytics, fund data platforms, client reporting, data pipelines, dashboards, and AI tools.

We are one of the most active AI-adopting engineering teams in Man Group — building LLM-powered agents, research tools with vector search, and AI integrations that our portfolio managers and analysts use daily. You'll have the opportunity to shape how AI is integrated into investment workflows.

The Role

This is a senior engineering role sitting at the intersection of Man Group's Discretionary (public markets) and Solutions technology teams in New York. You will be the primary NY-based engineer supporting portfolio managers, analysts and quants functions across both business lines.

The role spans Python data pipelines and analytics platforms serving Discretionary investment teams — equities, credit, and alternatives — alongside Python systems powering Solutions' fund analytics, portfolio management, and reporting infrastructure. You'll work hands-on building and operating production systems while acting as the key technical liaison for NY-based stakeholders.

Our Technology Stack

• Python (primary), TypeScript/React
• Data: Pandas, NumPy, Kafka
• Backend: FastAPI, Flask
• Frontend: React, Streamlit dashboards, Tableau
• Infrastructure: Kubernetes, Airflow
• AI tooling: Claude Code, LLM agents, vector search, RAG — we actively build and ship AI tools for our investment teams

Key Responsibilities 

Development & Delivery (70%)

• Build, extend, and maintain Python data pipelines using Pandas, NumPy, and internal libraries
• Develop and enhance portfolio analytics, risk reporting, and fund data platforms
• Contribute to AI-powered tools for investment teams — research databases with vector search, AI integrations for portfolio managers and analysts
• Build and maintain FastAPI and Flask backends and React/TypeScript frontends using our shared component libraries
• Deploy services to Kubernetes; manage Airflow DAGs for scheduled data workloads
• Collaborate with London and Sofia-based engineers on cross-team initiatives

Stakeholder Engagement (20%)

• Serve as the primary technical contact for NY-based Discretionary and Solutions stakeholders
• Gather requirements, translate business needs into technical solutions, and manage expectations
• Work directly with portfolio managers, analysts, and quants — understanding their workflows is as important as writing the code

Production Operations (10%)

• Own production stability for systems in your portfolio — investigate data quality issues, triage support requests, manage incident response
• Maintain documentation and operational processes

Key Competencies 

Essential

• 5+ years of professional software engineering experience with a strong delivery track record
• Strong Python: Well-tested, modular production code. Comfortable with dataclasses, type hints, OOP, design patterns
• Financial services experience — particularly portfolio management, risk, or investment operations
• Pandas/NumPy proficiency: Building efficient data pipelines and transformations at scale
• AI/LLM tooling — experience building with or integrating LLM-based tools. We're active early adopters of AI-assisted development and are building AI agents for our investment teams
• Solid testing discipline: pytest, unit tests, integration tests — you write tests as a matter of course
• Comfortable in a Linux environment with Git, virtual environments, and CLI tooling
• Strong communicator: You can explain technical decisions to non-technical stakeholders concisely, and you view stakeholder interaction as integral to good engineering — not overhead
• Self-directed: You manage your own priorities, flag blockers early, and drive work to completion with appropriate autonomy
• Degree in a STEM subject or equivalent practical experience

Advantageous  

• React/TypeScript for frontend development
• Experience with web APIs: Building and consuming RESTful services (FastAPI, Flask, or equivalent)
• C#/.NET familiarity — some Solutions systems are built in .NET. You won't be the primary .NET engineer, but being able to read and navigate the codebase is valuable
• Kubernetes & containerisation — deploying and troubleshooting services in k8s
• Airflow — building and maintaining scheduled data pipelines
• Distributed systems concepts — messaging architectures, event-driven design, caching strategies
• Experience working with geographically distributed teams — London will be your primary collaboration hub

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/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.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/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.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/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.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/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.

#LI-Hybrid

Hi, we're Oscar. We're hiring a Senior Analyst, Data Analytics, SIU to join our SIU team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

The Senior Analyst, Data Analytics, SIU partners across the organization to manage inefficiencies in the business. You will support teams in scoping, analyzing and monitoring performance of important financial and utilization metrics in service of our goals. The Senior Analyst, Data Analytics collaborates independently with stakeholders to define key questions and scope analyses. They may at times be called upon to speak to prepared analysis both internally and externally. This work aims to reduce medical waste and deliver more affordable and higher-quality health care for Oscar's members.

You will report into the Manager, SIU Data Analytics & Reporting.

Work Location: This is a remote position, open to candidates who reside in: Arizona, Florida, Georgia, Illinois, Iowa, Kansas, Michigan, Missouri, Nebraska, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas and Virginia. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area.

If you live within commutable distance to our New York City office (in Hudson Square) or our Tempe office (off the 101 at University Ave), you will be expected to come into the office at least three days each week. Otherwise, this is a remote / work-from-home role.  Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. 

Pay Transparency: The base pay for this role in the states of New Jersey and New York is: $86,628 - $109,761 per year. The base pay for this role in all other locations is: $75,265 - $98,785 per year.  You are also eligible for employee benefits, participation in Oscar's unlimited vacation program and annual performance bonuses.

You must be currently authorized to work in the United States on a full-time basis. Oscar will not sponsor applicants for this role.

Responsibilities:

• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues can understand, including packaging and presenting findings in a clear, concise and compelling manner
• Oversee the creation and maintenance of essential operational and analytical dashboards, and update and enhance them as our user's needs evolve
• Create models and tools that produce relevant insights to identify inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 1+ years of technical work experience using analytical tools and writing analytical reports
• 1+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by experience on at least 2 reporting projects requiring communication between technical and non-technical users
• Experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• Proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, finance or the insurance industry

Bonus points:

• 1+ years experience in preparing healthcare analytics and reporting
• 1+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO)
• 1+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Axsome Therapeutics is a biopharmaceutical company leading a new era in the treatment of central nervous system (CNS) conditions. We deliver scientific breakthroughs by identifying critical gaps in care and develop differentiated products with a focus on novel mechanisms of action that enable meaningful advancements in patient outcomes. Our industry-leading neuroscience portfolio includes FDA-approved treatments for major depressive disorder, excessive daytime sleepiness associated with narcolepsy and obstructive sleep apnea, and migraine, and multiple late-stage development programs addressing a broad range of serious neurological and psychiatric conditions that impact over 150 million people in the United States. Together, we are on a mission to solve some of the brain’s biggest problems so patients and their loved ones can flourish. For more information, please visit us at www.axsome.com and follow us on LinkedIn and X.

About This Role:

Axsome Therapeutics is seeking a Senior Manager, Field Reimbursement Analytics and Field Effectiveness (Neurology) to lead the operational infrastructure supporting our internalized Field Reimbursement Manager (FRM) team and Neurology sales operations. This role is critical to managing the transition from external vendor to internal operations while scaling support for increasing patient service volumes and complex incentive compensation requirements. The position requires deep technical expertise in data engineering, automation, and operational analytics to support field targeting, performance reporting, and incentive compensation administration. The ideal candidate combines strong programming and analytical capabilities with excellent communication skills to translate complex technical concepts into actionable insights for field leadership and internal stakeholders. This role reports directly to the Director of Field Effectiveness.

This role is based at Axsome’s HQ in New York City with an on-site requirement of at least three days per week. We are unable to consider candidates who are looking for fully remote roles. 

Job Responsibilities and Duties include, but are not limited to, the following:

• Manage targeting strategies and ongoing alignment changes for the FRM team, including weekly and monthly call plan updates, territory realignments and incentive compensation coordination
• Serve as primary liaison between FRM leadership, Commercial Operations, Market Access, and external vendors
• Build and maintain automated data infrastructure integrating CRM, claims, and PA submission/approval data to enable real-time patient service analytics and market access intelligence
• Create dashboards and reports for the FRM team showing PA initiation rates, submission volumes, approval rates by territory, market access trends, and field execution metrics
• Identify relevant KPIs and collaborate with field leadership to implement analytics that enable effective performance management and opportunity identification
• Develop advanced analytics linking PA rates, approval rates, and FRM activity patterns by geography to identify market access barriers and optimization opportunities
• Handle ad hoc sales analytics, reporting, and incentive compensation requests for Neuro sales teams
• Create targeted analyses to identify field execution opportunities based on CRM engagement data and secondary data sources (IQVIA/Symphony). Support continuous improvement of sales operations processes across the Neuro portfolio
• Support Sales leadership in the organization and coordination of National Sales Meetings, Manager Meetings, and Period-of-Action (POA) planning sessions
• Prepare executive-level presentations translating complex analytical findings into clear business recommendations
• Additional responsibilities as assigned

Requirements / Qualifications

• BS/MS/PhD in Engineering, Physics, Applied Physics, Statistics, Computer Science, or related quantitative field strongly preferred
• A minimum of 6 years of sales operations experience in the pharmaceutical or biotech industry (which may include work as a consultant or supplier to the industry)
• Expert-level SQL skills for complex queries, joins, and data manipulation. Advanced proficiency in Python (pandas, numpy) or R for data analysis and automation
• Advanced Excel capabilities including VBA/macros, Power Query, Power Pivot, and complex formula design
• Ability to work on site Monday, Tuesday & Thursday. We are unable to consider candidates who are looking for fully remote roles

Experience, Knowledge and Skills

• Excellent written and verbal communication skills with ability to translate complex technical concepts into clear business insights for all organizational levels
• Experience in Sales Force Design, Alignment, Targeting, Call Planning, and Incentive Compensation
• Experience in omnichannel planning and supporting Veeva CRM applications

Salary and Benefits:

The anticipated salary range for this role is $140,000 - $160,000. We encourage candidates of all levels to apply as there may be flexibility on final job title and responsibilities. The salary offer will be based on a variety of factors, including experience, qualifications, internal equity and location. Axsome offers a competitive employment package that includes an annual bonus, significant equity and a generous benefits package.

Axsome is committed to equal employment opportunity and providing reasonable accommodations to applicants with physical and/or mental disabilities. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, gender, sex, age, religion, creed, national origin, sexual orientation, gender identity, ancestry, citizenship, marital status, physical or mental disability, medical condition, veteran status, genetic information, or any other characteristic protected by federal, state, or local law. 

Axsome Therapeutics does not accept unsolicited resumes from recruiters or third-party recruitment agencies and will not pay placement fees for unsolicited candidates that are sent to hiring managers, the HR team or other Axsome team members. Only approved vendors who have been explicitly asked to support a specific search will receive access to our Applicant Tracking System to submit candidates for consideration.

Axsome Therapeutics is a biopharmaceutical company leading a new era in the treatment of central nervous system (CNS) conditions. We deliver scientific breakthroughs by identifying critical gaps in care and develop differentiated products with a focus on novel mechanisms of action that enable meaningful advancements in patient outcomes. Our industry-leading neuroscience portfolio includes FDA-approved treatments for major depressive disorder, excessive daytime sleepiness associated with narcolepsy and obstructive sleep apnea, and migraine, and multiple late-stage development programs addressing a broad range of serious neurological and psychiatric conditions that impact over 150 million people in the United States. Together, we are on a mission to solve some of the brain’s biggest problems so patients and their loved ones can flourish. For more information, please visit us at www.axsome.com and follow us on LinkedIn and X.

About This Role:

Axsome Therapeutics is seeking a Senior Manager, Field Effectiveness to build and lead the operational infrastructure for our new Long-Term Care (LTC) sales force targeting demand originating from facility-based settings. This role requires establishing entirely new analytical capabilities around facility-level data, transitioning from traditional physician-focused operations to facility-based commercial models. The position demands technical expertise in data integration, advanced analytics, incentive compensation and operational system design to support PointClickCare data onboarding. In addition this role will support an expanded Digital sales team on reporting, targeting to support geos that have solo coverage and incentive compensation. This role reports directly to the Director, Field Effectiveness.

This role is based at Axsome’s HQ in New York City with an on-site requirement of at least three days per week. We are unable to consider candidates who are looking for fully remote roles. 

Job Responsibilities and Duties include, but are not limited to, the following:

• Lead PointClickCare data integration project to establish facility-based analytics infrastructure, including designing data ingestion pipelines, normalizing facility/resident data structures, and establishing regular refresh cadences
• Build facility-level targeting and segmentation models incorporating census data, prescribing patterns, payer mix, and formulary status
• Develop facility profiling algorithms that identify high-opportunity targets based on disease prevalence, current treatment patterns, and competitive dynamics
• Build comprehensive LTC analytics infrastructure linking LTC rep activity to facility adoption. Implement cohort analysis frameworks to track facility product productivity over time
• Manage ongoing reporting, alignment, call planning, and IC design and admin for the LTC and Digital sales force
• Redesign DSAM targeting to optimize reach and frequency based on whether the hcp is currently covered by dual or single in person sales reps
• Create dashboards and reporting tools showing LTC sales force performance versus traditional team across key metrics, facility-level trends, rep performance, and formulary tracking
• Create ad hoc analyses to identify field execution opportunities based on CRM engagement data and secondary data sources (PCC, Symphony).
• Support LTC and DSAM Sales leadership in the organization and coordination of National Sales Meetings and POA planning sessions
• Collaborate with broader Commercial Operations team on cross-team optimization initiatives

Requirements / Qualifications

• BS/MS/PhD in Engineering, Physics, Applied Physics, Statistics, Computer Science, or related quantitative field strongly preferred
• A minimum of 6 years of sales operations experience in the pharmaceutical or biotech industry (which may include work as a consultant or supplier to the industry)
• Expert-level SQL skills for complex queries, joins, and data manipulation. Advanced proficiency in Python (pandas, numpy) or R for data analysis and automation
• Advanced Excel capabilities including VBA/macros, Power Query, Power Pivot, and complex formula design
• Ability to work on site Monday, Tuesday & Thursday. We are unable to consider candidates who are looking for fully remote roles

Experience, Knowledge and Skills

• Excellent written and verbal communication skills with ability to translate complex technical concepts into clear business insights for all organizational levels
• Experience in Sales Force Design, Alignment, Targeting, Call Planning, and Incentive Compensation
• Experience in omnichannel planning and supporting Veeva CRM applications

Salary and Benefits:

The anticipated salary range for this role is $140,000 - $160,000. We encourage candidates of all levels to apply as there may be flexibility on final job title and responsibilities. The salary offer will be based on a variety of factors, including experience, qualifications, internal equity and location. Axsome offers a competitive employment package that includes an annual bonus, significant equity and a generous benefits package.

Axsome is committed to equal employment opportunity and providing reasonable accommodations to applicants with physical and/or mental disabilities. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, gender, sex, age, religion, creed, national origin, sexual orientation, gender identity, ancestry, citizenship, marital status, physical or mental disability, medical condition, veteran status, genetic information, or any other characteristic protected by federal, state, or local law. 

Axsome Therapeutics does not accept unsolicited resumes from recruiters or third-party recruitment agencies and will not pay placement fees for unsolicited candidates that are sent to hiring managers, the HR team or other Axsome team members. Only approved vendors who have been explicitly asked to support a specific search will receive access to our Applicant Tracking System to submit candidates for consideration.

Axsome Therapeutics is a biopharmaceutical company leading a new era in the treatment of central nervous system (CNS) conditions. We deliver scientific breakthroughs by identifying critical gaps in care and develop differentiated products with a focus on novel mechanisms of action that enable meaningful advancements in patient outcomes. Our industry-leading neuroscience portfolio includes FDA-approved treatments for major depressive disorder, excessive daytime sleepiness associated with narcolepsy and obstructive sleep apnea, and migraine, and multiple late-stage development programs addressing a broad range of serious neurological and psychiatric conditions that impact over 150 million people in the United States. Together, we are on a mission to solve some of the brain’s biggest problems so patients and their loved ones can flourish. For more information, please visit us at www.axsome.com and follow us on LinkedIn and X. 

 About This Role 

Axsome Therapeutics is seeking a Senior Manager, Digital Centric Commercialization (DCC) Analytics and Operations to lead the evolution of our Next Best Action capabilities and manage exponentially increased complexity from our multi-brand, multi-team commercial portfolio. This highly technical role requires expertise in machine learning, optimization algorithms, and commercial analytics to transition DCC Intelligence from static, single-model suggestions to a continuous test-and-learn framework. The position is critical for implementing multi-team optimization that allocates promotional activities across overlapping sales forces to maximize profitability while avoiding customer fatigue. 

This role is based at Axsome’s HQ in New York City with an on-site requirement of at least three days per week. We are unable to consider candidates who are looking for fully remote roles.  

 Job Responsibilities and Duties include, but are not limited to, the following: 

• Build linear optimization engine that allocates promotional calls across multiple teams to overlapping HCP targets.  

• Develop objective functions maximizing expected revenue while incorporating constraints including call capacity, contact limits, customer fatigue thresholds, and strategic imperatives; responsible for managing this process on a quarterly basis 

• Design and implement continuous test-and-learn framework for Next Best Action (NBA) suggestions that include business rules, ML models, and hybrid approaches 

• Design comprehensive DCC performance dashboard with leading and lagging indicators 

• Develop suite of advanced predictive models including HCP propensity to prescribe, churn risk etc. 

• Create ad hoc analyses to identify field execution opportunities and commercial optimization insights based on CRM engagement data, promotional response patterns, and secondary data sources (IQVIA/Symphony) 

• Support Sales leadership in the organization and coordination of National Sales Meetings, Manager Meetings, and Period-of-Action (POA) planning sessions 

 Requirements / Qualifications 

• BS/MS/PhD in Engineering, Physics, Applied Physics, Statistics, Computer Science, or related quantitative field strongly preferred 

• 6 years of sales operations experience in the pharmaceutical or biotech industry (which may include work as a consultant or supplier to the industry) 

• Expert-level SQL skills for complex queries, joins, and data manipulation. 

• Advanced proficiency in Python (pandas, numpy) or R for data analysis and modeling 

• Advanced Excel capabilities including VBA/macros, Power Query, Power Pivot, and complex formula design 

 Experience, Knowledge and Skills 

• Strong understanding of key pharmaceutical data sources (IQVIA, Symphony, claims data) and data structures to produce actionable insights 

• Excellent written and verbal communication skills with ability to translate complex technical concepts into clear business insights for all organizational levels 

• Experience in hcp segmentation, targeting and resource allocation. 

 Salary & Benefits  

The anticipated salary range for this role is $140,000 - $160,000. We encourage candidates of all levels to apply as there may be flexibility on final job title and responsibilities. The salary offer will be based on a variety of factors, including experience, qualifications, internal equity and location. Axsome offers a competitive employment package that includes an annual bonus, significant equity and a generous benefits package. 

Axsome is committed to equal employment opportunity and providing reasonable accommodations to applicants with physical and/or mental disabilities. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, gender, sex, age, religion, creed, national origin, sexual orientation, gender identity, ancestry, citizenship, marital status, physical or mental disability, medical condition, veteran status, genetic information, or any other characteristic protected by federal, state, or local law.  

Axsome Therapeutics does not accept unsolicited resumes from recruiters or third-party recruitment agencies and will not pay placement fees for unsolicited candidates that are sent to hiring managers, the HR team or other Axsome team members. Only approved vendors who have been explicitly asked to support a specific search will receive access to our Applicant Tracking System to submit candidates for consideration.

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

About the Position

We are looking for a Data Engineer to turn messy, real-world datasets into reliable inputs for research and trading. Jane Street depends on data from a wide variety of sources to understand markets and the global economy—think world news, decades of weather patterns, deidentified credit card spending, or packet captures of stock exchange market data feeds. Clean, well-structured data is the difference between noise and a profitable trading signal. 

You'll work closely with trading desks to identify Jane Street's data needs, evaluate datasets, and build pipelines that ingest and transform external data. You'll figure out what data means and how best to represent it. We build our own tools and software when needed, so you'll also help shape the systems you use every day.

This is a collaborative role, but you'll own your work from end to end. It requires a mix of engineering, data analysis, and product sense. You'll develop deep expertise in your data domains and use that understanding to decide what's worth building next.

About You

• Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code
• Proficient with SQL or DataFrame libraries like pandas or Polars
• Intellectually curious with a meticulous approach to data investigation; you enjoy the detective work required to make sense of unfamiliar datasets
• A clear and concise communicator

Prior experience with financial data is helpful but not required. We’re happy to hire talented engineers and teach them what they need to know.

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

Junior Quant Developer — Backtesting, Simulation & Research, Productionise Research (C++/Python)

Role Overview

We’re hiring a junior Quant Developer to help productionise research into robust, high-performance trading systems. You’ll work closely with Quant Researchers and senior engineers to convert Python research code into production C++, build and optimise backtesting / simulation infrastructure, and support strategy development using L3 market data across multiple venues.

This is a hands-on, engineering-heavy role in a fast-moving environment: you’ll own components end-to-end and contribute directly to research velocity and trading PnL.

Key Responsibilities

• Productionise research models into C++: translate Python prototypes into efficient, maintainable C++ production code.
• Backtesting & simulation: build and improve simulation systems that reflect real market mechanics (order book, fills, cancels, exchange rules).
• L3 market data handling: ingest and process high-volume tick/order-level feeds; create reliable feature pipelines from raw exchange data.
• Performance optimisation: improve latency and throughput of backtests/sims (profiling, memory optimisation, data structures, parallelism where appropriate).
• Research support tooling: create utilities for data inspection, experiment tracking, run orchestration, and post-trade analytics in Python.
• Debugging & correctness: investigate mismatches between simulation and production behaviour; diagnose edge cases and implement fixes with strong test coverage.
• Cross-team collaboration: work daily with researchers and infra/exec engineers to ship improvements from idea → test → production.

Requirements

• Education: Bachelor’s or Master’s from a top university in Computer Science, Engineering, Math, Physics, or similar.
• 0-3 years experience in quantitative finance or other relevant data-intensive industries working with C++
• Strong working knowledge of C++ (memory, ownership, STL, performance-aware coding).
• Experience: demonstrable evidence of hands-on systems work in C++ handling large-scale data (internships, research labs, competitive projects, open-source).
• Comfortable with Python for analysis, tooling, and debugging (pandas/numpy/Jupyter a plus).
• Exposure to quantitative finance, eg through internships/university societies, including market microstructure and L3/order book data.
• Clear “builder mindset”: you like owning problems end-to-end, shipping incrementally, and iterating quickly.