About the Team

The Discovery team is organized around the north star of building an AI scientist — a system capable of solving the long-horizon reasoning challenges and core capabilities needed to push the scientific frontier. The team trains large-scale models, runs complex multi-week experiments, and builds novel products at the intersection of AI and science.

About the Role

As a Technical Program Manager on the Discovery team, you will own the systems and programs that determine how fast our research moves: compute planning, scientific RL environment health, and the vendor pipelines that supply them, with scope to incubate new programs in domains like bio R&D. Strong candidates should have an ML engineering or research background and have grown into program leadership. You'll need real technical depth: the ability to debug data pipelines, read RL transcripts to spot issues, and make allocation and quality decisions in real time when experimental or production runs hit problems. You'll need organizational effectiveness in equal measure: the ability to navigate a fast-growing organization, quickly identify the critical people and teams across research, infrastructure, product, and data operations, and coordinate across them without losing velocity.

Join us in our mission to build AI systems that push the frontiers of science and benefit humanity.

Responsibilities

• Manage Discovery's compute planning across supervised learning (SL), reinforcement learning (RL), and sandboxing workloads, including forecasting, allocation, prioritization, and efficiency improvements. Partner with central compute planning to ensure Discovery's needs are represented and met.
• Monitor the health of scientific RL environments (quality, reward integrity, failure rates) and drive issues to resolution.
• Expedite the external vendor pipeline for RL environments, including quality review, reward design, and production integration.
• Work with research teams across life sciences, STEM, and other scientific domains to translate research goals into roadmaps that advance AI scientist capabilities.
• Establish processes and frameworks that bring structure to an unstructured research setting without slowing researchers down.
• Collaborate with research leads, infrastructure engineers, and data operations to identify blockers, prioritize competing needs, and make technical trade-off decisions.

You May Be a Good Fit If You:

• Have a background in ML engineering, ML research, or STEM R&D before transitioning to technical program management
• Have deep, hands-on experience with ML training pipelines, RLHF systems, and large-scale data infrastructure in production.
• Have a track record of building execution plans and inventing high-leverage processes that reduce operational overhead and let researchers focus on research.
• Are a fast learner who builds deep contextual understanding in unfamiliar technical domains and can contribute meaningfully to discussions with researchers.
• Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in a fast-moving research setting
• Have excellent stakeholder management and communication skills, with the ability to influence senior technical staff through clarity, competence, and consistent delivery.
• Are excited about the potential for AI to accelerate scientific discovery

The Team

Our engineering team builds systems that interact with some of the most complex software  ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. 

We are looking for a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize. While we are a remote-first company, the nature of this role requires candidates to be based in the San Francisco Bay area/PST time zone.

What You’ll Do

• Work closely with some of the most sophisticated ML / GenAI teams in the world.
  • You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.
• Advise on GenAI and ML best practices 
• Give ML and LLM product demos to technical and business stakeholders
• Run strategic business reviews for customers in partnership with our sales team
• Interface with our pre-sales engineering team to gather client goals and KPI’s.
• Partner with our product and engineering teams to help drive the product roadmap
• Spearhead new opportunities within existing accounts to help drive expansions.

What We’re Looking For

Note: Even if you do not check every single box, we still encourage you to apply! 

• Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
• Comfortable working in public Cloud environments (AWS, Azure, GCP)
• Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
• Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
• Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
• Understanding of GenAI concepts and application evaluation + development lifecycle  
• Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
• Strong Communication Skills - Ability to simplify complex, technical concepts.
• A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

Bonus Points, But Not Required

• Previous engineering experience in:
  • Data Science
  • MLOps
  • ML Frameworks
  • LLM / Agentic frameworks
• Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
• Prior experience working with applications deployed with Kubernetes
• Prior experience demoing technical products to both business and technical audiences

The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.

While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.

About the Role

We’re looking for a Forward Deployed Marketing Data Scientist to partner closely with our AI Decisioning customers and internal engineering teams to ensure that AI-driven marketing campaigns deliver measurable, compounding impact. This role is uniquely cross-functional: you’ll spend time diagnosing model behavior, tuning ML levers, analyzing incrementality, exploring customer data, and explaining insights to marketers and executives.

Marketing teams come to Hightouch to transform how they operate. Instead of planning campaigns weeks ahead on a calendar, AI Decisioning continuously learns customer preferences and executes 1:1 messaging that adapts in real time. Your mission is to make sure that these AI agents perform at their best—and to help customers understand why they are performing the way they are.

You’ll work alongside ML engineers, product managers, Solutions Consultants, and some of the world’s most recognizable brands to improve campaign performance, debug experiments, and identify opportunities for additional lift. Roughly 30% of your time will be customer-facing and 70% deep analytical and modeling work.

No two days are the same, but you can expect to:

Own diagnostics, insights, and tuning for AI Decisioning campaigns

• Explain why AI Decisioning is driving lift using counterfactuals, incrementality breakdowns, and cohort analysis.
• Debug performance issues, iterate on reward functions, and ensure the agent’s recommendations align with customer goals.
• Investigate experiment setups (send volumes, reachability, channel constraints) and surface actionable recommendations.

Work deeply with data in notebooks and customer warehouses

• Pull down historical data to run exploratory analyses using Polars / Pandas in Jupyter notebooks
• Modify and improve customer feature matrices to unlock deep personalization.
• Conduct deeper warehouse-level SQL analyses when insights aren’t available in the UI.

Build lightweight tooling that enables scale

• Create templates, notebooks, scripts, and repeatable workflows that improve how we analyze performance across customers.
• Identify systemic gaps and influence the direction of ML reporting and introspection.

Communicate ML concepts clearly to non-technical stakeholders

• Present model insights and recommendations to marketers, analysts, and executives.
• Explain how the decision engine handles cold start, message transfer learning, exploration vs. exploitation, and more.
• Partner closely with Solutions Consultants to identify and drive new opportunities for uplift.

What We’re Looking For

• Strong ability to perform deep exploratory data analysis in Python (Polars / Pandas, Jupyter notebooks).
• Ability to write and interpret SQL for customer warehouse analysis.
• High-level understanding of ML modeling concepts (features, hyperparameters, reward functions, training windows).
• Excellent communication skills; able to explain technical reasoning simply and confidently to marketers.
• A customer-first attitude with high ownership and urgency when resolving issues.

Bonus Points

• Experience setting up and analyzing marketing experiments such as A/B, multivariate tests.
• Prior experience in an applied ML, data science, analytics engineering, or forward-deployed role.
• Experience building lightweight internal tools or scripting solutions.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. We focus on impact and potential for growth more than years of experience. The salary range for this position is $140,000 - $220,000 USD per year, which is location independent in accordance with our remote-first policy.

Interview Process

We have limited inbound applications to one application per candidate. You will be auto-rejected if you apply to multiple roles. Please only apply to the position you are most qualified for.

Our interview process evaluates the most important dimensions of the role: analytical depth, customer communication, first-principles problem solving, and alignment with Hightouch’s values.

Intro Call [15–30m]

Introductory call with either a member of our recruiting team or the hiring manager to get to know each other and see if the role could be a good mutual fit.

Take Home Data Analysis Exercise + Review Session [45m]

You’ll complete a short take-home assignment focused on exploratory data analysis of an example dataset. In the live review, you’ll walk through your approach, explain your reasoning, and present your findings as if you were guiding a customer through your analysis. We’re looking for clarity of communication, rigor of thinking, and the ability to turn data into actionable insights.

Experiment Design & Analysis Session [90m]

A hands-on session where we collaboratively design and evaluate an experiment end-to-end. This includes:

• Defining the experimental goal and how success should be measured
• Identifying the most relevant context and features to use in modeling
• Interpreting example results and diagnosing performance patterns
• Recommending next steps and communicating tradeoffs

Hiring Manager Interview [30m]

Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.

About this role

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive. 

As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human-in-the-loop training to create high performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real-world impact. You will independently design and implement solutions and work with the cross-functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end-to-end.

What you’ll do

• Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire’s product listings.
• Use deep learning, LLM fine tuning, and human-in-the-loop training to automatically detect and address issues with high accuracy.
• Act as a lead on the cross-functional Listing Quality pod, thinking end-to-end about brand and retailer experiences.

Qualifications

• 3+ years of industry experience using machine learning to solve real-world problems
• Experience with relevant business problems (e.g. e-commerce)
• Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human-in-the-loop machine learning)
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• The ability to design and implement ML solutions without supervision
• Strong communication skills and the ability to work in a highly cross-functional team 

Great to Haves:

• Master’s or PhD in Computer Science, Statistics, or related STEM fields is highly recommended
• Previous experience in listing quality for e-commerce
• Previous experience in supervised fine tuning of multi-modal LLMs
• Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact

Salary Range

Canada: the pay range for this role is $180,000 to $247,500 per year.

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

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About this role

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive. 

As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human-in-the-loop training to create high performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real-world impact. You will independently design and implement solutions and work with the cross-functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end-to-end.

What you’ll do

• Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire’s product listings.
• Use deep learning, LLM fine tuning, and human-in-the-loop training to automatically detect and address issues with high accuracy.
• Act as a lead on the cross-functional Listing Quality pod, thinking end-to-end about brand and retailer experiences.

Qualifications

• 3+ years of industry experience using machine learning to solve real-world problems
• Experience with relevant business problems (e.g. e-commerce)
• Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human-in-the-loop machine learning)
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• The ability to design and implement ML solutions without supervision
• Strong communication skills and the ability to work in a highly cross-functional team 

Great to Haves:

• Master’s or PhD in Computer Science, Statistics, or related STEM fields is highly recommended
• Previous experience in listing quality for e-commerce
• Previous experience in supervised fine tuning of multi-modal LLMs
• Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact

Salary Range

San Francisco: the pay range for this role is $211,000 to $290,500 per year.

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

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications.

As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.

As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

You will:

• Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  
• Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
• Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
• Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
• Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.
• Stay deeply connected to the research community, understanding major trends, and helping set them.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
• A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.
• Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.

About Scale

At Scale AI, 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 abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team 

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. 

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have: 

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally. 

Nice to have:

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax. 
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH 
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities.

In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models.

You will:

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Ideally you’d have:

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills

• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale Labs, Research Scientist — AI Controls and Monitoring

As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.

Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.

As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might:

• Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs;
• Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected;
• Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps;
• Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation.

Ideally you’d have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance.
• Practical experience conducting technical research collaboratively. You should be comfortable designing control and monitoring experiments for AI systems, building prototype systems, and quickly turning new ideas from the research literature into working prototypes.
• A track record of published research in machine learning, particularly in generative AI.
• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development.
• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Experience with runtime monitoring, anomaly detection, or observability for ML systems.
• Familiarity with AI control or alignment research (e.g., scalable oversight, interpretability, debate).
• Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.

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

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

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

What you’ll do

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

What we’re looking for

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

Preferred qualifications

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

What success looks like

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

Scale Labs, Research Scientist — Agent Robustness

As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.

Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.

As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: 

• Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them;
• Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment;
• Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use;
• Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents.

Ideally you’d have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance.
• Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes.
• Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches.
• A track record of published research in machine learning, particularly in generative AI.
• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development.
• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Hands-on experience with agent evaluation frameworks such as SWE-bench, WebArena, OSWorld, Inspect, or similar tools.
• Experience with red-teaming, prompt injection, or adversarial testing of AI systems.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs. You will help define what "good" looks like in generative AI, driving research that informs both our internal roadmap and the broader research community. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs.

You will:

• Drive research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Mentor and guide research scientists and engineers, providing technical leadership across cross-functional projects.
• Stay deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience tech leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale’s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Ideally, you’d have:

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes.

• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).

• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.

• Strong written and verbal communication skills, along with the ability to work effectively across teams.

Nice to have:

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.

• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.

• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.

• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.

• Proficiency in cloud-based ML development, with experience in AWS or GCP environments.

Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Tech Lead Manager of the LLM Evals Research team, you will lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs. 

You will:

• Lead a team of highly effective research scientists and research engineers on LLM evals.
• Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
• Remain deeply involved in the research community, both understanding trends, and setting them
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience supporting and leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale Labs, Research Scientist — Frontier Risk Evaluations

As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.

Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.

As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: 

• Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities;
• Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems;
• Publish evaluation methodologies and write technical reports for policymakers.

Ideally you’d have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance.
• Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes.
• A track record of published research in machine learning, particularly in generative AI.
• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development.
• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Experience in crafting evaluations and benchmarks, or a background in data science roles related to LLM technologies.
• Experience with red-teaming or adversarial testing of AI systems.
• Familiarity with AI safety policy frameworks (e.g., NIST AI RMF, EU AI Act, Korea AI Basic Act).

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.

We are looking for an AI Developer Advocate to join our Developer Relations team. In this role, you will help promote MongoDB's artificial intelligence (AI) capabilities. As more developers choose MongoDB as their data platform, your responsibilities will include directly engaging with the community, building strategic partnerships with AI companies, creating inspiring resources and content, and collaborating with a global team of skilled Developer Advocates.

You will empower developers—from startups to Fortune 500 companies—to integrate advanced data and AI capabilities into their applications and solutions. If you are passionate about helping builders explore the possibilities of AI and enjoy cultivating a vibrant developer ecosystem, we invite you to join us in shaping the future of development on MongoDB.

Our Developer Relations teams are distributed across the globe, with most members working remotely. This position will be based in the San Francisco Bay Area. To see what our team is doing, check out our content on YouTube, Dev, and Medium.

We are looking to speak to candidates who are based in San Francisco for our hybrid working model.

Candidate Profile

We are excited to welcome an influential individual to our team who is already a well-established voice in AI. From your experience over the past few years, we’ll see you in videos and at events sharing technical insights, leading discussions, and inspiring others to effectively use AI and ML capabilities. You’ve also created articles, tutorials, and hands-on workshops to teach builders best practices and equip them to leverage AI in their apps. 

At the foundation of your passion and expertise is a love to equip others. Our ideal candidate will have at least 3 years of experience in a builder role, such as a data scientist or developer, where they crafted AI solutions in production. They will have 8+ total years of experience through any combination of builder role (such as data scientist or developer), educator role (such as developer advocate or developer educator), or customer-facing role (such as solution architect). 

Our ideal candidate will also have connections with AI companies and communities in the San Francisco Bay Area. You will work with key AI partners to create content and partner on virtual and in-person events that showcase how MongoDB is part of the larger AI ecosystem. 

You are an effective teacher who can explain complex topics in a simple and easy-to-understand way. Along with an appreciation for the key AI-related features of our platform, such as vector search and Voyage AI, you will also develop a strong understanding of MongoDB's core capabilities, data modeling, and emerging trends in our industry.

Though the expertise you bring will be unique, our team is built to work together to share knowledge and help each other grow. You will work with others at all levels, supporting peer reviews of code, demos, sessions, and other content. You should have a genuine passion for equipping other developers to be more productive and successful. 

Position Expectations

Below are examples of the types of work you will be doing. Your mix of activities will vary week to week based on priorities and event schedules. 

• Build on a solid foundation of ML/AI expertise, adding to your database experience to become a MongoDB expert
• Expand your knowledge of embedding models and rerankers to become an expert in Voyage AI
• Collaborate with our events and field teams to engage developers and founders in the Bay Area at meetups, events, hackathons, and startup houses
• Speak at strategic AI events and lead workshops at high-profile conferences such as AWS re:Invent 
• Create and update tutorials, articles, videos, and workshops along with their associated workflows or workflows or code examples
• Provide feedback to our Product and Technology team, serving as the voice of the developer as new products are scoped and planned
• Regularly interface with Partner Managers to identify opportunities to work with key AI partners to create content and partner on virtual and in-person events that showcase how MongoDB is part of the larger AI ecosystem 
• Partner with our community team to support engagement with third-party and first-party user groups (MUGs), Champions, and influencer programs across the region
• Lead one-hour sessions (both virtual and in-person) with customer teams to evaluate their AI use cases and provide recommendations on how they can better utilize MongoDB

Requirements

• Expertise in building AI or ML solutions and comfortable building agentic solutions
• Advanced familiarity with several AI coding and workflow tools, and how platforms are recommended through content, preference, and integration
• Expertise with one or more complementary programming languages (Python or JavaScript preferred)
• Knowledgeable and connected in the Bay Area AI ecosystem
• Prolific author of content (tutorials, how-to guides, readmes) and associated code to help developers learn
• Established portfolio or active contributor to AI examples and Agent Skills in GitHub
• Engaging presenter at in-person events, videos, webinars, or live streams 
• Up to 25% of time traveling to Bay Area engagements (like meetups, events, hackathons, and startup houses)
• Up to 10% of time traveling outside of the Bay Area for industry events 

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions 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.

Req ID: 1273376493

Staff GenAI Research Scientist - Retrieval

P-1214

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description 

As a Staff Research Scientist on the Enterprise Agents team, you will be responsible for keeping up with the latest developments in Agent Context, Information Retrieval, Knowledge Assistants, RAG, Embeddings, and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Staff Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on Information Retrieval for reusable Agent components, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches.
• Drive research and technical strategy across enterprise retrieval and search, including workspace search, vector search.
• Drive algorithmic innovations for Retrieval within Large Language Models. 
• Experience with Agent Benchmarks for retrieval, text-embeddings and LLM Data Quality. 

What We Look for

• 5+ years of 
• PhD in Computer Science or related field with strong foundations in Natural Language Processing and Information Retrieval 
• Developing and implementing methods that extend and improve model capabilities, reliability, and safety. 
• Strong preference for candidates with first-author publications at top ML/systems conferences (EMNLP, ICLR, ACL, NeurIPs) focused on optimization or efficiency.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description 

As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Sr. Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
• Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.

What We Look for

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
• Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role: 

As a Senior Data Scientist for Go-to-Market at fal, you will be the analytical backbone of our revenue organization. Embedded directly with the GTM function, you will own the metrics that tell us how our pipeline is performing, how our sales team is executing, and where the next dollar of revenue is most likely to come from.

This is a high-leverage, high-visibility role. GTM leadership will look to you for the answers - on rep performance, quota attainment, pipeline health, AM coverage, and segment economics - and you'll shape both the questions we ask and the systems we build to answer them. You'll partner closely with Product Intelligence and Data Engineering as part of fal's center-of-excellence data team, while acting as the embedded specialist for everything GTM.

Key responsibilities:

• Own the metrics and reporting that drive sales execution at fal: pipeline health, quota attainment, conversion rates, sales cycle, AM coverage, and segment-level economics.
• Partner directly with the sales leadership and rev-ops to translate strategic questions into measurement frameworks and weekly operating cadences.
• Build the data foundations that make GTM analytics first-class: account-manager tracking, territory and quota models, opportunity-stage instrumentation, and rep-level performance views.
• Run rigorous deep-dives - win/loss, lead source effectiveness, segmentation, expansion drivers - that change how GTM allocates time and headcount.
• Shape the CRM, internal tooling, and downstream data models that everyone in GTM depends on, and set the standards for how GTM data is captured, joined, and trusted.

Requirements:

• 5+ years of experience in data science or analytics roles, with at least 3+ years specifically in GTM, RevOps, or sales analytics at an enterprise or B2B SaaS company. This is a hard requirement - we are looking for someone who has seen many variations of this problem and can run with it.
• Advanced SQL and proficiency in Python for analytics, modeling, and experimentation.
• Deep familiarity with Salesforce data, pipeline mechanics, quota and territory models, and the operational rhythms of an enterprise sales org.
• Strong proficiency with dbt and modern analytics stacks; comfort partnering with data engineering on production-grade pipelines.
• Proven ability to operate as an embedded analytics partner - building trust with sales leadership and translating ambiguous strategic asks into clear measurement.
• Demonstrated bias for action; you set up the dashboard, write the SQL, and ship the framework yourself when needed.
• A track record of shipping data products that change behavior, not just dashboards that get viewed once.

Nice to have:

• Experience supporting both self-serve/PLG and enterprise sales motions.
• Experience working on developer-facing or API products.
• Familiarity with usage-based pricing and consumption-driven sales motions.
• Early-stage or fast-scaling environment experience.

Compensation

• $180,000-225,000 plus equity + benefits (This range is across 2 levles Senior and Staff)

Location

• San Francisco, CA (willing to consider remote for Senior and Staff levels)

What we offer at fal

• Interesting and challenging work

• A lot of learning and growth opportunities

• We are currently hiring in downtown San Francisco.

• We offer relocation assistance to San Francisco.

• Health, dental, and vision insurance (US)

• Regular team events and offsites

We are looking for a Senior Software Engineer specializing in Machine Learning to join our Revenue ML team at Discord. This team partners with our revenue product groups, focusing on both consumer revenue and our emerging Ads initiative. This role will specifically contribute to our Ads ML efforts, helping to build and scale ML capabilities in areas such as ads measurement, targeting, and delivery ranking.

As part of this team, you will play a critical role in developing foundational ML models that enhance ad relevance, optimize performance, and drive revenue. This is a unique opportunity to work on an early-stage Ads ML platform and have a direct impact on the business's success. Our tech stack includes Python, ML frameworks like PyTorch and TensorFlow, large-scale data infrastructure, and real-time ad-serving technologies.

What You'll Be Doing:

• Design, develop, and deploy machine learning models for ads targeting and ranking.
• Develop sophisticated ML solutions such as identity graph to enhance ad targeting.
• Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click).
• Improve ads targeting and ranking by leveraging both on-platform and off-platform signals.
• Collaborate cross-functionally with product, engineering, and business teams to define and execute on the Ads ML roadmap.
• Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making.
• Drive research and implementation of state-of-the-art ML techniques in the field of online advertising.

What You Should Have:

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• 3+ years of experience specifically in Ads ML (ads ranking, personalization, optimization, privacy-compliant user modeling, targeting, or measurement).
• Strong proficiency in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with applied deep learning (e.g transformers, embedding models).
• Proven track record of designing, implementing, and scaling ML-driven ad systems in real-world applications.
• Experience working with real-time ML inference, A/B testing, and optimization frameworks.
• Experience translating ML evaluation results and performance metrics into actionable product roadmap items.
• Ability to connect business objectives to ML solutions, with the flexibility to shift focus toward the highest-impact problems as priorities evolve.

Bonus Skills:

• Strong understanding of performance advertising and how ML impacts revenue and advertiser retention.
• Knowledge of ad tech industry standards and ads ecosystem including targeting, retrieval, ranking, pacing, frequency, auction, etc.
• Experience with large-scale recommendation systems.
• Experience with large-scale data infrastructure and distributed computing

The US base salary range for this full-time position is $220,000 to $247,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Hex's user base is continuing to grow rapidly. We are hiring a Sales Engineer to partner with potential customers to support their Hex evaluations.

About the role

Hex is redefining how teams work with data - combining notebooks, apps, BI, and AI-native workflows into a single collaborative analytics platform. Companies like Anthropic, Cursor, and Brex rely on Hex as a core part of how their data teams operate.

We’re at an exciting stage of growth. Hex is scaling rapidly, with strong momentum in the mid-market and SMB segments. This is a high-impact moment to join: our go-to-market motion is accelerating, our AI capabilities are evolving quickly, and Sales Engineers play a central role in shaping how we win.

As a Sales Engineer, you will leverage your product, ecosystem, and technical expertise to shape how our potential customers evaluate and adopt Hex. You will partner with the Sales team to help prospects understand the challenges in their current state, connect Hex’s value to those challenges, own the technical evaluation, and set them up for long-term success as a customer. This is a consultative, highly technical position where you’ll influence deal strategy, inform product direction, and act as the voice of the customer.

If you want to learn more about the team, what we do, and how we work, please check out our team page!

What you will do

• Serve as a trusted technical advisor to data teams (think: Data Scientist or Analyst writing SQL and Python) and build strong relationships to help them get the most out of Hex during their evaluations
• Own the technical sales cycle and work with end users throughout the Sales cycle from discovery and product demos through trials, and proofs of concept
• Partner closely with Account Executives to develop opportunity-level strategy, execute evaluations, and share feedback to improve your partnership
• Inform the product roadmap by synthesizing product feedback from prospects to share with internal Engineering & Product teams
• Project manage the architecture, security, and technical reviews that prospects require
• Develop content to support users who are a part of evaluations ie. demo projects, documentation, videos, etc.
• As needed, travel to customer on-sites and marketing events to deliver demos and build strong customer relationships

Who you might be

You might be a fit for this role if you have:

• 5+ years of professional work experience
• 3+ years in a Sales Engineer, Solutions Engineer, or similar customer-facing technical role
• Experience working with Mid Market customers (250-2500 employees)
• Experience with land POC/Technical Sales Motions
• Familiarity with data science tooling and workflows, including Python, SQL, and BI tools (Bonus points if you have spent lots of time in notebooks, SQL IDEs, or app-building frameworks.)
• A strong track record of talking to customers - from IC users to senior stakeholders - and solving their problems
• You're an excellent communicator who builds empathy, shares feedback, and grows successful relationships with internal and external stakeholders
• A generalist technical skillset: you don't need a CS degree, but should have a passion and interest for technology and be a creative problem solver
• Experience or interest in working in an early-stage startup environment

In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off.

The OTE (base + variable) range for this role is: $175,000 - $200,000.

The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the process.

By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.

Title: Actuarial Data Scientist

Location: San Francisco Bay Area, CA / Austin, TX / Dallas, TX / Morristown, NJ (Flexible / Hybrid)

Reporting to: Director, Actuarial

Open to Relocation? We’ve Got You Covered: 

This role is open to candidates willing to relocate to one of our hub locations. Hippo offers relocation assistance to support your move, so you can focus on doing impactful work—not the logistics of getting here.

About Hippo:

Hippo exists to protect the joy of homeownership. We believe that insurance should protect the things you treasure through an intuitive, modern experience. We provide tailored insurance coverage and preventative maintenance plans that keep you protected throughout your homeowner journey. We’ll also help you find coverage for everything life brings—from auto to flood—reimagining how you care for your home.

About This Role:

We’re hiring an Actuarial Data Scientist to lead loss cost modeling for Hippo's Homeowners program. This role will own the design, development, and deployment of predictive models for frequency and severity, ensuring strong alignment with pricing strategy and business objectives. You'll build and scale Python-and SQL-based tooling that embeds expected loss ratio and segmentation analytics into reusable, production-ready workflows. In addition to leading loss cost modeling, you'll have the opportunity to expand the team's modeling capabilities across the demand and aggregation models to inform broader pricing and business mix decisions. 

About You:

You are a hands-on leader with a strong background in loss modeling. You bring structure to ambiguity, enjoy building scalable work, and take pride in developing people on your team. You think critically about model maintenance cost and you balance scientific rigor with practical business impact. You communicate clearly, document thoroughly, and operate with a strong sense of ownership.

What You’ll Do:

• Lead a homeowners insurance modeling, setting clear priorities, technical standards, and best practices while fostering a culture of ownership, rigor, and continuous improvement 
• Own the design and annual build of our by-peril loss models
• Expand modeling capabilities across conversion, retention, and aggregation to inform pricing strategy, business mix, and portfolio performance 
• Implement and scale models within our Airflow-based Python modeling pipeline, ensuring robust testing, validation, reproducibility, and long-term maintainability
• Develop reusable analytical tooling and workflows that improve efficiency, consistency, and scalability across the actuarial team
• Partner cross-functionally with Insurance Product, Underwriting, and Engineering to translate complex modeling insights into clear business recommendations and ensure successful production deployment

Must Haves:

• Bachelor’s degree in statistics, mathematics, data science, or another quantitative field
• 5+ years of experience in data science, analytics, or actuarial modeling within personal lines P&C insurance
• Strong experience with loss cost modeling; exposure to demand, underwriting, and/or claims modeling
• Knowledge of actuarial principles as they relate to insurance pricing
• Advanced proficiency in Python and SQL
• Excellent communication skills and ability to build trust with stakeholders at all levels

Nice to Haves:

• Actuarial credentials - ACAS/FCAS
• Master’s degree in a quantitative discipline
• Experience working in modern data platforms, including familiarity with cloud infrastructure (e.g., AWS) and workflow orchestration tools (e.g., Airflow)

The base pay range for this role is $145,000- $160,000 for our Texas (Austin and Dallas regions). The SF Bay Area (and New Jersey) base pay range for this role is $155,000- $180,000. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, location, business needs and market demands. 

Benefits and Perks:

Hippo treats its team members with the same level of dedication and care as we do our customers, which is why we’re fortunate to provide all of our Hippos with: 

• Relocation Assistance - Support available for qualified candidates relocating to one of our hub locations
• Healthy Hippos Benefits - Multiple medical plans to choose from and 100% employer covered dental & vision plans for our team members and their families. We also offer a 401(k)-retirement plan, short & long-term disability, employer-paid life insurance, Flexible Spending Accounts (FSA) for health and dependent care, and an Employee Assistance Program (EAP) 
• Equity - This position is eligible for equity compensation  
• Training and Career Growth - Training and internal career growth opportunities 
• Flexible Time Off - You know when and how you should recharge 
• Little Hippos Program - We offer 12 weeks of parental leave for primary and secondary caregivers 
• Hippo Habitat - Snacks and drinks available and catered lunches for onsite employees 

Hippo is an equal opportunity employer, and we are committed to building a team culture that celebrates diversity and inclusion.  

Hippo’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Hippo applicant who requires reasonable accommodations during the application process should contact the Hippo’s People Team to make the need for an accommodation known. 

We are seeking a high-impact Staff Data Scientist to play a leading role on our data needs to bridge the gap between advanced research and production-grade ML systems. You will be a key technical leader and partner to our Research Scientists, driving the evolution of our AI algorithms through rigorous data science methodologies, strategic data curation, and cross-functional leadership.

Job Responsibilities:

• Vision & Cross-Functional Leadership: Engage with cross-functional teams (Product, Research, Engineering, and Process Engineering) and help guide the overarching vision for data analysis, curation, and annotation to improve our AI models. Drive the definition of algorithm and data requirements necessary to deliver on end-point objectives.
• Data Campaigns and Annotation Strategy: Introduce best practices and efficient processes to enable multiple, large-scale annotation campaigns for continuous AI product improvements. Spearhead the strategic design of data campaigns needed to advance AI algorithms.
• Advanced Data Curation & Management: Develop comprehensive data curation strategies for improvements to AI models. Partner with MLOps to architect data management systems for algorithm training and performance validation, and establish data dashboards and monitoring reports.
• Performance Evaluation and Statistical Analysis: Establish frameworks and develop tools to rigorously evaluate the strengths and weaknesses of model iterations across patient populations. Design and oversee data analyses using statistical techniques to illuminate the performance of our AI algorithms.

Required Qualifications:  

• Education: Masters or PhD Degree in Engineering, Computer Science, Statistics, Data Science or related degree.
• Work Experience: 7+ years (or 5+ with PhD) of proven track record in Data Science, Machine Learning, Computer Vision, or Image Analysis in industry. Have a wealth of experience from working on complex, real-world AI problems in medical imaging or computer vision requiring careful consideration of data needs.
• Software: Proficient in Python, including statistical and machine learning packages (e.g. scipy, sklearn, statsmodels, seaborn) with a commitment to writing clean, reproducible and scalable code. Familiarity with image and 3D processing tools like VTK and ITK, and visualization tools like 3DSlicer and MITK, a plus.
• Statistics: Understanding of standard statistical techniques and ability to apply appropriate statistical methods to a range of data structures; experience with medical imaging data a plus.
• Data Management: Experience working with data lakes, SQL/No SQL Databases, AWS Cloud Storage, Tableau dashboards.
• AI & Medical Imaging: Expertise in deep learning and machine learning models in production. Strong experience working with medical imaging data (CT and vascular imaging) is highly preferred.
• (Preferred) Proficiency in Agentic AI Tools: Experience integrating generative AI and agentic tools into daily workflows to act as a force multiplier—accelerating coding, prototyping, and complex data analysis—while demonstrating the critical judgment required to rigorously evaluate AI outputs for accuracy.
• Communication: Excellent written and verbal communication. Detail orientated but able to describe complex topics in a manner that is digestible to a broad audience. Ability to distill complex analyses into interpretable and actionable findings.
• Commitment: Committed to the success of the team and successful completion of project - 75% confidence / 100% committed.
• Influence without Authority: Able to build trust and obtain cross-functional alignment across departments.

A reasonable estimate of the base salary compensation range is $220,000 to $280,000, bonus, and equity. #LI-IB1 #LI-Hybrid

About the Role
As a Senior Research Associate Scientist in the Protein Engineering group, you will be a crucial member of our interdisciplinary team, comprising highly creative and talented individuals with exceptional expertise in protein characterization and engineering. This group is responsible for enabling AI drug discovery efforts and optimizing lead molecules. You will work collaboratively with protein designers, biologists, and other drug discovery team members.

We’re looking for an extraordinary library builder who can design, generate and scale complex DNA assemblies for our protein engineering and display teams. This role requires extensive experience with combinatorial, designed and naive library building with the relevant microbiological and protein level expertise to express & qualify them once built. This hands-on role is best for someone who can keep NGS, protein biochemistry, and DNA assembly needs in mind when building complex libraries at speed. 

About You
You are an enthusiastic protein biochemist who takes pride in your bench execution skills. Your passion lies in display technology, drug discovery and developing novel treatments for patients. You are conscientious, detail-oriented, and organized. Collaboration comes naturally to you, and you thrive in a fast-paced environment where pushing the boundaries of what is possible is the norm.

What You'll Do and Learn

• Design and apply multiple innovative selection techniques utilizing synthetic libraries, like phage, yeast display, and mammalian display. 
• Utilize FACS sorting, plate-based screening, and NGS to identify binders.
• Setup and use automation to further rank leads for affinity and function. 
• Collaborate with cross-functional teams to troubleshoot protein reagents. 
• Train and mentor junior team members, providing guidance on experimental design, data analysis, and troubleshooting.
• Maintain accurate and detailed records of experiments, protocols, and results in accordance with company standards and regulatory requirements.
• Interpret and present scientific findings at research meetings. Provide scientific input and propose follow-up experiments.
• Collaborate and communicate across diverse research teams to successfully achieve scientific goals.
• Contribute to scientific publications, patents, and presentations to disseminate research findings both internally and externally.

Qualifications

• Bachelor of science or master degree in Molecular Biology, Protein Biochemistry, or related fields with 5+ years of industrial experience.
• Hands-on experience with yeast display system and library building.
• Cloning complex assemblies with multi-part golden gate, gibson, and other techniques
• Experience with DNA synthesis CROs.
• High proficiency in yeast display to protein targets, soluble and membrane.
• Proficiency in molecular and cell biology techniques, such as DNA extraction, PCR, enzymatic DNA treatments and library preparation QC for NGS..
• Mammalian tissue culture.
• Antibody engineering and discovery experience.
• Flow cytometry experience (both analytical and sorting). 
• Excellent analytical and problem-solving skills, with meticulous attention to detail.
• Strong written and verbal communication skills, with the ability to effectively present complex scientific concepts to both technical and non-technical audiences.
• Ability to work effectively in a collaborative, multidisciplinary team environment, fostering cooperation and knowledge-sharing among team members.
• Experience using LIMS and Benchling systems.

Nice to have Skill(s)

• Experience in protein purification techniques (including affinity, ion exchange, HIC, SEC) and in chromatography hardware and software (Cytiva AKTA, Agilent HPLC).
  
  

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $110,000 - $138,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role

You are an enthusiastic protein biochemist who takes pride in your bench execution skills. Your passion lies in display technology, drug discovery and developing novel treatments for patients. You are conscientious, detail-oriented, and organized. Collaboration comes naturally to you, and you thrive in a fast-paced environment where pushing the boundaries of what is possible is the norm.

Responsibilities

• Build, adapt, and automate display systems to facilitate AI antibody design. 
• Establish, develop, and/or optimize cutting edge technologies to enable data generation at scale for AI model training or evaluation
• Design and apply multiple innovative selection techniques to provide data at scale based on ML training needs. 
• Design, setup, optimize, and use automation to characterize affinity and function at the clonal level. 
• Contribute to the preparation of technical reports and presentations.
  
  

Qualifications

• Significant hands-on experience with protein display techniques such as yeast and/or phage display. Experience in library design, build, panning/sorting and validation. 
• Bachelor of Science or Master’s degree in Molecular Biology, Biology, Biochemistry, or related fields with 2-6 years of industrial experience.  . 
• Familiarity with antibody binding assays and automating them (ELISA, SPR, FACS).
• Proficiency in molecular and cell biology techniques, including mammalian tissue cell culture, and basic skills in molecular biology labs.
• Working knowledge of software and programming for large data set analysis.
• Excellent analytical and problem-solving skills, with meticulous attention to detail.
• Strong written and verbal communication skills, with the ability to effectively present complex scientific concepts to both technical and non-technical audiences.
• Ability to work effectively in a collaborative, multidisciplinary team environment, fostering cooperation and knowledge-sharing among team members

Schedule Flexibility: Due to the nature of experimental workflows, this role will require availability on weekends (approximately every couple of weeks). 

Employment Type: Contract

Contract Duration: 9 Months

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $45-$60 hourly; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
Xaira Therapeutics is seeking a lab-based Senior Scientist in Inflammation and Immunology to join our Biology & Pharmacology department. This role is ideal for someone who thrives in a hands-on research environment, has experience working with primary human or mouse immune cells and ex vivo tissue systems, and is excited to help shape therapeutic program strategy.

In this role, you will investigate disease biology and drug mechanisms, generate actionable data, and contribute to advancing therapeutic programs through cross-functional collaboration.

What You’ll Do

• Drive preclinical programs by designing and executing in vitro and in vivo studies that explore disease biology, target validation, and lead candidate development.
• Identify knowledge gaps, ask critical mechanistic questions to guide program direction, and evaluate novel targets and therapeutic strategies.
• Dissociate human tissue biopsies into single-cell suspensions or establish human tissue slice cultures for downstream functional or phenotyping assays.
• Lead immune profiling and functional characterization using high-parameter flow cytometry (15+ colors or spectral platforms), functional assays (T cell activation, differentiation, proliferation, suppression), and molecular/cytokine profiling (MSD, Luminex, qPCR, RNA sequencing).
• Translate experimental data into actionable insights and clearly communicate findings and recommendations to cross-functional teams.

What We’re Looking For

• PhD in Immunology or a related field with 3+ years of relevant experience; industry experience preferred.
• Track record of impact through publications, presentations, or applied research.
• Hands-on experience with primary human or mouse immune cells and/or ex vivo tissue systems.
• Strong expertise in flow cytometry, including high-parameter panel design, execution, and data analysis.
• Proven ability to independently plan, execute, troubleshoot, and interpret experiments.
• Highly organized, with the ability to manage multiple workstreams in a fast-paced environment.
• Clear communicator who can distill complex data into actionable insights.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $140,000 - $170,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
We are seeking an Associate Scientist to join our High-Throughput (HTP) team to support the discovery and development of innovative protein therapeutics. This role focuses on the design and execution of HTP expression, purification, and characterization campaigns. You will work at the interface of biochemistry and automation, collaborating closely with our robotics and data teams to advance candidate molecules from in silico design to physical validation.

About You
The successful candidate works effectively both independently and as part of cross-functional teams. Experience collaborating with discovery, process development, and analytical departments is highly desirable. We require an adaptable scientist with strong communication skills and the ability to present data across team and departmental levels. You should excel in fast-paced environments, managing multiple responsibilities and shifting priorities. You are expected to work effectively both independently and as part of a team to drive complex projects forward. This is a hands-on role suited for a scientist who is passionate about advancing drug discovery and development through innovation and scientific rigor.

Key Responsibilities

• High throughput protein expression, purification and characterization from multiple systems including cell free systems and mammalian is the primary responsibility.
• Drive team throughput and data quality by developing novel strategies for parallel protein processing. Key responsibilities include optimizing expression and purification workflows and conducting quality control and functional assays for proteins used in therapeutic development and in silico design.
• Excellent record keeping and organization is a must
• The experience and flexibility to work on upstream medium scale expression and downstream purification is a plus.
• Perform analytical characterization of purified proteins using HPLC, CE-SDS, and icIEF to ensure high-quality candidates for therapeutic development.

Qualifications

• B.S. (6+ years) or M.S. (6+ years) in a relevant scientific discipline; industrial experience preferred. (PhD (2+ years)
• Proven expertise in high-throughput (HTP) protein production, with a specific focus on cell-free protein expression (CFPE) and/or mammalian transient expression systems.
• Understanding of the biophysics of protein-protein interactions, protein chemistry, experience in the molecular biology and biophysical techniques essential for protein work is required.
• Demonstrated hands-on experience with high-throughput (96/384-well) expression and purification workflows.
• Proven track record of independent project management and cross-functional collaboration.
• Dedicated to inclusive leadership and maintaining a respectful, diverse team environment.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $101,000 - $126,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

• Develop multimodal foundation models spanning image and molecular data
• Design approaches that unify representation learning and generative modeling
• Train large-scale models on structured, high-dimensional datasets
• Explore cross-modal alignment, prediction, and generation
• Build scalable systems for data processing, training, and evaluation
• Work in a research-driven environment with evolving problem definitions

• Experience with representation learning (self-supervised, contrastive, masked modeling, etc.)
• Experience with generative modeling (diffusion, autoregressive models, VAEs, or related approaches)
• Proficiency in Python, ML frameworks, and CI/CD (PyTorch, JAX, etc.)

• Work on multimodal learning or cross-domain representation learning
• Experience with image data, molecular / omics-like data, or both
• Familiarity with large-scale training

• Exposure to biological or scientific datasets
• Experience with paired or partially aligned multimodal data
• Comfortable working in open-ended, evolving problem spaces

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $170,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role

We are seeking a driven Scientist and experimentalist who combines strong hands-on molecular biology skills with a creative, critical, and builder-oriented mindset. This role is focused on assisting in the design, construction, and iteration of novel screening platforms and experimental workflows that enable biological discovery at scale.

The ideal candidate is a self-starter who enjoys working in ambiguous problem spaces, thinks deeply about experimental design, and takes ownership of turning early ideas into robust, reproducible systems. You will work collaboratively with other teams, including automation, engineering, and computation, to invent new ways of generating high-quality biological data.

Key Responsibilities

• Develop novel antibody screening technologies and experimental platforms, from early proof-of-concept through scalable, robust workflows
• Design, implement, and optimize screening assays, including biochemical, molecular, and cell-based readouts
• Assist multidisciplinary platform development efforts as a biochemical expert through microbial and mammalian cell line engineering (e.g. cloning, genome editing, expression optimization)
• Apply data-driven and critical thinking approaches to troubleshoot, refine, and improve workflows, enhancing throughput, robustness, and interpretability
• Clearly document experimental workflows, present results, and contribute to shared platform standards while maintaining flexibility for rapid exploration
• Collaborate closely with cross-functional partners (automation, engineering, computation) to integrate biology, data, and technology into cohesive systems

Required Qualifications

• PhD in Molecular Biology, Bioengineering, Biochemistry, or a related field with 1+ years of industry experience, or
  B.S. or M.S. with 8-10 years of relevant industry or applied research experience
• Prior work on platform, workflow, or method development, especially in exploratory or early-stage settings (see examples under Bonus Skills)
• Experience with antibody discovery and engineering workflows, including panning, enrichment, or display-based screening approaches
• Experience with assay development, optimization, and experimental troubleshooting
• Strong hands-on experience in molecular cloning and DNA manipulation
• Experience with cell-line engineering (e.g. E. coli, yeast, mammalian or related systems)
• Demonstrated ability to work independently, think critically, and drive conclusive experiments
• Strong organizational skills and attention to experimental detail

Preferred Qualifications

• Experience with functional antibody screening or protein–protein interaction assays
• Familiarity with high-throughput or semi-automated screening systems
• Experience working with data-rich experimental systems
• Comfort operating in fast-moving, collaborative, and partially undefined problem spaces

Nice to Have

Experience in one or more of the following areas would be a plus:

• Spatial biology technologies (e.g. spatial transcriptomics, in situ or imaging-based assays)
• Single-cell technologies, including single-cell sequencing or high-content single-cell assays
• Microarray-based assays or other multiplexed screening formats
• Microfluidics, particularly for screening, assay miniaturization, or single-cell applications
• High-content imaging or phenotypic screening
• Experience studying or manipulating cell-internal signaling pathways (e.g. receptor signaling, transcriptional regulation, immune signaling, stress responses, or related pathways)
• Protein expression, secretion, or trafficking assays

Compensation: Annual

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $110,000 - $138,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

Location: San Francisco, CA (Hybrid) 

What is Verse? 

Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.

Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.

The Role

Verse is seeking a Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and energy risk management. You will shape the machine learning and data modeling foundations that Verse's software is built on. For example, you might spend a cycle deploying electricity market price forecasting pipelines for new regions, developing solar production anomaly detection models, or creating scalable tools for benchmarking energy project financial performance.

Key Responsibilities

• Lead End-to-End Data Science Projects: Own and drive projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions.
• Statistical & Machine Learning Modeling: Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models) to support decision-making and enhance product capabilities.
• Analytics Engineering & Data Modeling: Perform complex data transformations and develop well-structured data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets.
• Software Development & Productionization: Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems in a cloud-based environment while leveraging AI coding tools to accelerate development.
• MLOps: Contribute to Verse’s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production.
• Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows.

What We're Looking For (Minimum Qualifications)

• Master’s degree in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and 2+ years of professional experience in data science or machine learning; or
• Bachelor’s degree and 4+ years of professional experience in data science or machine learning
• Strong foundation in statistical modeling and machine learning, including time series forecasting and model evaluation
• Experience deploying and maintaining models in cloud-based environments (e.g., AWS, GCP, or Azure) using MLOps practices
• Strong Python expertise, including experience with scientific computing and ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
• Hands-on experience in orchestrating complex data transformations (e.g. Airflow, Dagster, dbt)
• Strong software engineering practices (version control, testing, code reviews, CI/CD)
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders

What Will Make You Standout (Preferred Qualifications)

• Experience in energy, climate tech, or related domains (not required)
• Familiarity with optimization methods or operations research
• Experience developing probabilistic forecasting models and quantifying uncertainty
• PhD in a quantitative field

What Makes Verse a Great Place to Work? 

• Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
• Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
• Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
• Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations

Base Pay Range

$146,000 - $172,000

This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.

Benefits and Employee Perks 

• Competitive compensation and equity grant at a high-growth start up 
• Comprehensive benefits package including medical, dental and vision insurance, and 401k 
• Flexible hours and unlimited PTO 
• Diverse and inclusive working environment 

Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.

Verana Health, a digital health company that delivers quality drug lifecycle and medical practice insights from an exclusive real-world data network, recently secured a $150 million Series E led by Johnson & Johnson Innovation – JJDC, Inc. (JJDC) and Novo Growth, the growth-stage investment arm of Novo Holdings. 

Existing Verana Health investors GV (formerly Google Ventures), Casdin Capital, and Brook Byers also joined the round, as well as notable new investors, including the Merck Global Health Innovation Fund, THVC, and Breyer Capital.

We are driven to create quality real-world data in ophthalmology, neurology, urology, and oncology to accelerate quality insights across the drug lifecycle and within medical practices. Additionally, we are driven to advance the quality of care and quality of life for patients. DRIVE defines our internal purpose and is the galvanizing force that helps ground us in a shared corporate culture. DRIVE is: Diversity, Responsibility, Integrity, Voice-of-Customer and End-Results. Click here to read more about our culture and values.

Our headquarters are located in San Francisco and we have additional offices in Knoxville, TN and New York City with employees working remotely in AZ, CA, CO, CT, FL, GA, IL, LA, MA, MN, NC, NJ, NV, NY, OH, PA, SC, TN, TX, VA, WA, D.C. All employees are required to have permanent residency in one of these states. Candidates who are willing to relocate are also encouraged to apply. 

Candidates based in the Bay Area, New York City, and Knoxville, Tennessee will be give priority consideration. For these locations, the position will follow a hybrid work model, with 3 days per week in office and the remaining days working from home. 

*Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.*

Job Title: Quantitative Scientist

Why This Role Matters:

The Quantitative Scientist will be responsible for executing and providing oversight and guidance on the analytical, statistical and epidemiological components of Verana research projects and data quality initiatives. The primary function of this role will be to conduct, guide, and manage the analytical execution of Verana research projects . The Quantitative Scientist will collaborate cross-functionally to build research capacity and adopt quality standards across Verana's business units.  This position requires an experienced individual with knowledge of statistics, ability to develop and review code with a solid understanding of coding best practices, a strong understanding of epidemiological study designs, as well as excellent communication and interpersonal skills.  In addition, you should be able to continually unearth and present interesting trends that have clinical, research, and business importance for our customers and oncology patients at large.  You will be joining a friendly, high performing and diverse research team with backgrounds in public health, health economics, biology, and statistics.  This role will report to the Vice President, Research.

WHAT WILL YOU GAIN

• Expertise in the oncology real-world data industry, a fast-growing segment of health data
• Experience executing oncology research and analytical/statistical methods to answer key questions for patients, providers, and life science companies

WHAT TO EXPECT IN YOUR FIRST YEAR AT VERANA:

In thirty days, you will:

• Understand the full suite of Verana’s research offerings and analyses
• Understand the research team’s GitHub repo and analysis template 

In three months, you will:

• Contribute to internal and external meetings related to Verana research and analyses
• Gain expert understanding of Verana’s data model  
• Implement clinical specifications on real-world data and add to the suite of functions available for analyses

In six months, you will:

• Personally execute analytical research projects
• Contribute to the development of project collateral, research protocols, abstracts, posters and manuscripts
• Guide and mentor data scientists and analysts 

In one year, you will:

• Lead the analytical execution of Verana’s research projects for life science, provider, and regulatory partners 
• Scope projects to determine feasibility, estimated costs, and expected timelines
• Provide guidance to Verana’s client partners in the use of Verana’s data model and analytical/statistical methodologies 

HOW YOU WILL IMPACT VERANA

• Lead the design and development of Verana research studies from a statistical and analytical perspective
• Contribute to the development of protocols and statistical analysis plans 
• Develop code and produce results as defined in protocols and statistical analysis plans
• Collaborate with physicians, statisticians, data scientists, business leaders, and others within and outside Verana to conduct research projects including observational studies, pharmacoeconomic analyses, and other relevant study types
• In partnership with the Research Team, communicate studies in progress and demonstrate results to key stakeholders through high quality abstracts, posters, and publications
• Manage and mentor a team of data analysts and data scientists, including reviewing code and analytical output
• Contribute to the evolution of Verana’s quality assurance framework, including identifying data quality issues during analysis
• Maintain current and in-depth understanding of real-world data analytical methodologies, along with the ability to lead and mentor internal team members in successfully executing them

WHAT YOU BRING TO THE TABLE

• Masters degree in computer science, statistics, applied math, econometrics, MPH, or similar quantitative field
• 3+ years of relevant research experience in the field of oncology (post-graduation)
• Experience working with real-world data sourced from electronic health records
• Experience analyzing claims data 
• Advanced knowledge of SQL, R programming, and version control (git)
• Deep understanding and experience with descriptive statistics, logistic and multivariate regression analysis, power calculations, propensity score analysis, and survival analysis
• Significant experience developing protocol documents, statistical analysis plans (SAPs), and manuscript tables and figures
• Evidences well-developed conceptual and integrative thinking with ability to access internal and external resources as needed 
• Project implementation and execution, including engagement with key stakeholders, with a high degree of autonomy
• Mentors junior analysts in HEOR and statistical analysis methodologies
• Excellent written and verbal communication skills
• Strong organizational and time management skills 
• Works well independently, as a team member, and as a team leader 
• Comfort working in a fast-paced, dynamic environment

NICE TO HAVE

• Experience implementing data science methodologies
• Understanding of data quality metrics and/or quality management systems

Benefits:

• We provide 100% health, vision, and dental coverage for employees 
• 401K Match
• Flexible vacation plans 
• $700 learning and wellness annual stipend 
• Headspace meditation app access

Final note:

You do not need to match every listed expectation to apply for this position. Here at Verana, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

Caution to Job Applicants: Be vigilant against potential scams. Verana Health will never ask for payment or personal information upfront. Verify company details, cross-check job offers, and trust your instincts. Any legitimate job offer will be received by a Verana Health email account (not via gmail, text or other means) Report suspicious activities to protect yourself and others in the job-seeking community.

#LI-REMOTE

About the Role
Our Data Science team is a world-class data, applied science, and ML organization that leads data-driven decision-making and the conversational AI efforts for the entire company. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented data scientists in a high-performance and high-impact culture.

What You’ll Accomplish

• Lead the development of statistical, econometric, optimization, and machine learning models for a range of applications in our messaging and AI product offerings
• Design and execute experiments, interpret results, and draw actionable conclusions
• Use data to understand product performance, identify improvement opportunities, and define product/team roadmaps
• Present findings to senior leadership to inform and influence business decisions
• Collaborate with cross-functional teams across product, engineering, client services, and sales to drive business value from ideation to production

Your Expertise

• Ph.D., M.S. or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields
• Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis and testing, and model development
• Ability to use Python to work efficiently at scale with large data sets
• Advanced proficiency in SQL

Nice to Haves

• 4+ years of industry experience as an Applied or Data Scientist or equivalent
• Familiarity with advanced statistical inference, experimentation, and causal inference methods
• Econometric experience with pricing and promotion optimization
• Expertise in customer lifetime value modeling
• Experience in personalization systems and cross-sectional cohort modeling
• Background in operations research (e.g., scheduling or assignment problems)
• Knowledge of advanced topics in XGBoost modeling

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 - $300,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MDK1

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The Impact You’ll Be Contributing to Moloco: 

Moloco Commerce Media (MCM) 

• enables marketplaces to leverage the recent advances in AI for delivering tailored ads to relevant users, driven by first-party data. MCM has established a strong product market with several leading marketplaces working with us to show relevant ads. 
• We’ve established our MCM’s product market fit with strong interest in our product. MCM is an important product that is key to Moloco’s continued success and is in a high growth phase. The science team supports MCM's growth by supporting the launch of new features through modeling, algorithmic and analytical excellence. As a Senior Applied Scientist focused on ML in MCM, you will have the opportunity to work on and improve various components of our ad-tech stack including ranking, retrieval, auction/bidding and budget pacing. We highly value prior experience in working in ad-tech. 

What You’ll Do:

• Conduct deep-dive analysis to influence R&D decisions and strategies: analyze large datasets, extract valuable signals out of noise, and design state of the art machine learning models to optimize Moloco’s complex bidding system. 
• Design and deploy advanced optimization approaches to improve our ad-delivery: identifying the best ranking, retrieval and bidding strategies that strike the right balance between ROI and revenue trade-offs. 
• Leveraging the latest advances in deep learning to evaluate and improve our search quality. 
• Build the right metrics for product areas and guide ramps with domain data expertise: improve performance monitoring of a large and complex ads ecosystem by establishing the right metric framework, and understanding cause-and-effect relationships across drivers; guiding ramp decisions through rigorous A/B testing.

Basic Qualifications:

• MS or Ph.D. degree in a quantitative discipline with exposure to advanced modeling and statistical techniques. 
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Experience with one or more programming languages including Python, Java or C++ 
• Past experience with ad-tech/ranking/retrieval and/or search quality is preferred.

Preferred: 

• 4+ years of experience (industry or postgraduate) in Data Science, with a heavy focus on experimentation and causal inference in a high-growth tech environment (AdTech  preferred).
• Demonstrated leadership and self-direction. Able to seek out new business questions and effectively scope projects to improve our ML model performance.

The impact you'll be contributing to Moloco:

Creatives are one of the highest-leverage levers in Moloco Ads: they shape what users see, how they interact, and ultimately how much value advertisers extract from our platform. As formats grow more complex (video, playables, rich HTML) and surfaces diversify across exchanges, SDK, and new inventory types, our creative systems must do more than just serve assets — they must learn, adapt, and guide advertisers toward better outcomes.

This space sits at the intersection of ML/bidding, supply, and UI/UX for advertisers. Strong product decisions here directly influence company toplines, ROAS and advertiser retention. At the same time, weak creative strategy can quietly erode performance, create operational noise, and diminish trust in our optimization systems. We need a Staff Product Data Scientist who can bring structure, rigor, and long-term thinking to this inherently noisy problem space.

The person will be the analytical and product thought partner for the Creatives team, owning the data narrative across ideation, launch, and iteration of creative features and strategies. This is not a “support” role; it is a co-owner of the creative roadmap.

Here’s what you’ll be working on:

This role is critical to ensuring that Moloco’s creative systems become a long-term competitive advantage, not just a collection of formats and features.

• Be recognized as a thought leader in the creative domain, someone whose perspective is actively sought when making high-stakes product calls. For example, influence which creative problems we choose to solve, not just how we measure the outcomes.
• Establish a trusted, repeatable framework for measuring creative impact that the organization rallies around. This will enable PM/ENG to ship creative features faster and with more confidence, backed by well-designed experiments and clear success criteria.
• Reduce ad-hoc fire drills by building durable monitoring, diagnostics, and documentation that make creative performance and adoption more transparent.

Minimum Qualifications

• Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Physics) or equivalent practical experience.
• 8+ years of experience (or PhD + 6 YoE) in data science, product analytics, or a closely related quantitative field, including significant time as a product-facing IC.
• Proven track record of partnering with Product and Engineering to shape roadmaps, define success metrics, and drive decisions through data.
• Demonstrated ability to operate with high ownership and autonomy, including scoping ambiguous problems and driving them to closure.
• Comfort working across time zones and with distributed teams, using strong async communication and documentation habits.

Preferred Qualifications

• Graduate or PhD degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Physics) or equivalent practical experience with 10+ years of experience in related fields. 
• Prior experience in ad tech, marketing science, or related domains where creatives, auctions, or optimization systems are central to performance.
• Hands-on experience with creative analytics (e.g., format benchmarking, asset-level performance analysis, interaction or engagement modeling).
• Experience collaborating closely with ML teams to design, evaluate, and iterate on model features and policies.
• Excellent communication skills: ability to synthesize complex analytical findings into simple, actionable narratives for technical and non-technical audiences.

The Impact You'll Be Contributing to Moloco:
Growth Data Science is a global team of data scientists who work with internal and external stakeholders to improve the effectiveness of Moloco Ads and help advertisers achieve their business goals. As a Senior Data Scientist you will act as a leader within the team, working across a portfolio of top strategic advertisers and taking ownership of high impact product initiatives. This is a critical and highly cross-functional role with diverse responsibilities;

• Advertiser engagement; engaging with advertisers to understand their business objectives, measurement strategies and identifying opportunities for Moloco to drive business value
• Measurement consultation; consulting with advertisers on measurement methodologies, helping them to understand nuances between different measurement solutions (MMP attribution, incrementality, MMM) and supporting the activation of Moloco incrementality solutions
• Insights generation; data collection, analysis and effective communication of learnings and recommendations to multiple levels of stakeholder up to C-Level
• Campaign optimization: partnering with internal and external teams on analysis and testing to identify opportunities to improve Moloco campaign effectiveness
• Product development; collaborating with key stakeholders across Moloco product and engineering teams to help improve our products and services based on market insights and advertiser feedback
• Product activation; collaborating with Moloco business teams to develop activation strategies to unlock product performance and drive adoption across advertiser groups  

Minimum Requirements:

• Education: Bachelor's degree or equivalent practical experience.
• Statistics: must have knowledge and experience in experimental design, hypothesis testing, and various statistical analysis such as regression or time-series analysis.
• Programming: experience in Python and SQL is required.
• Comfortable balancing multiple projects simultaneously and effectively prioritizing work based on business needs.
• Excellent verbal and written communication skills. Ability to distill complex concepts and information into simple recommendations, presenting to stakeholders at various levels of seniority and technical expertise.
• Experienced building partnerships with advertisers and business teams to grow an Ads business using data and analytics.
• Proven ability to own projects end-to-end and operate in ambiguous problem spaces, able to develop creative solutions to complex problems.
• Demonstrated leadership and self-direction.
• Experience in external client facing role
• Experience in ad-tech, or advertising environment 

Please note: This position is not eligible for immigration sponsorship. 

Company Overview

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation.

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark. 

AI Governance Team, Responsible AI/ML Data Scientist

We are seeking a Vice President, Responsible AI/ML Data Scientist on our AI Governance Team who combines technical expertise in Data Science and Machine Learning with a strong advisory lens to help drive trustworthy AI solution development across Accordion's practices. In this role, you will serve as an internal subject matter expert, embedding responsible AI principles and controls across the AI development lifecycle to drive validated, explainable, compliant, and auditable AI solutions. Drawing on your experience with AI policy, regulatory standards, and testing methodologies, you will translate governance requirements into actionable and testable playbooks that teams across the business can apply consistently. This position is critical to co-designing AI solutions with embedded Responsible AI practices aligned to Accordion's AI Governance principles. As Accordion scales AI capabilities across its practice areas, this role will provide the validation rigor and oversight needed to ensure we develop AI solutions our clients and firm can trust.

This position must be based in our New York City, Chicago, or San Francisco office and is a hybrid role with the flexibility to work remotely 2 days a week.

This position is not eligible for immigration sponsorship.

What You’ll Do:

Governance & Technical Standards

• Translate AI governance, regulatory, and compliance requirements into testable operational Responsible AI playbooks with quantifiable standards for transparency, accuracy, fairness, privacy, and accountability — tailored to Accordion's AI solutions and business model
• Develop frameworks and guidance supporting systematic evaluation, testing, and risk mitigation that enable auditability, lineage, and transparent decision records
• Build evaluation frameworks that guide data scientists and engineering teams in developing, testing, and monitoring AI systems requirements; define mitigation strategies, detection methodologies, and acceptability thresholds
• Develop and implement testing principles for bias detection, model robustness evaluation, privacy preservation, and AI/privacy regulation alignment across different AI architectures and data types
• Establish benchmarks and governance processes aligned with industry standards (e.g., NIST AI RMF, EU AI Act, ISO 42001) that enable auditable AI transparency and explainability against applicable regulations and Accordion standards

Testing & Validation

• Collaborate with data science and engineering teams across our AI solution practices to embed responsible AI controls throughout the development lifecycle
• Develop repeatable testing and validation playbooks and evaluation frameworks for use across practice areas
• Pressure test AI solutions for accuracy, reliability, and trustworthiness, including output anomaly detection, logging, and observability mechanisms
• Develop methods to produce model cards and support audit trails for outputs across Accordion's business practice pillars and Client solutions

Cross-Functional Advisory

• Act as the firm's internal subject matter expert on Responsible AI topics including algorithmic fairness, transparency, privacy preservation, safety protocols, and risk mitigation strategies across the AI lifecycle
• Partner with Legal/Privacy/Risk, Technology, and D&A teams to translate regulatory requirements into actionable and measurable controls and governance structures
• Collaborate with teams developing AI solutions on risk-informed design decisions — advising on model selection, testing approaches, and appropriate guardrails
• Establish Responsible AI frameworks and operational playbooks that demonstrate alignment with evolving AI regulations (e.g., EU AI Act, GDPR, CCPA) and sector-specific requirements
• Monitor emerging AI regulations, industry standards, and responsible AI methodologies — translating insights into actionable internal design guidance
• Where applicable, support higher-risk or higher-profile engagements and AI product development where rigorous testing and evaluation of AI solutions is required

You Have:

• 5+ years of hands-on experience in data and ML, including developing, deploying, and evaluating solutions using a range of skillsets (e.g., statistics, machine learning, NLP, data visualization)
• Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, Statistics, or a related quantitative field
• Proven technical experience in regulated or complex industries with demonstrated collaboration across Legal/Risk/Compliance, Security, and AI/ML engineering teams
• Track record of operationalizing responsible AI through technical development frameworks, testing protocols, and quantitative evaluation that embed fairness, transparency, and accountability into production AI systems
• Strong programming proficiency in Python, R, or similar languages, with experience in ML frameworks and responsible AI tooling
• Understanding of AI and privacy regulations and standards — including EU AI Act, NIST AI RMF, GDPR, CCPA, and ISO 42001 — and the ability to translate regulatory mandates into technical controls
• Exceptional communication skills with the ability to convey complex technical and regulatory considerations to non-technical stakeholders, including leadership and cross-functional teams

Preferred Qualifications:

• Advanced degree (Master's) in Computer Science, Data Science, Statistics, Information Systems, Engineering, or a related quantitative discipline
• Consulting experience at a leading management or professional services firm
• Direct experience working with Legal/Privacy/Compliance teams on AI, data governance, or emerging technology matters
• Familiarity with responsible AI tooling, red teaming platforms, or model evaluation frameworks

You Are:

• Energized by ensuring AI systems that solve complex business challenges are built responsibly — with fairness, accuracy, transparency, and privacy by design embedded from the start
• A cross-functional collaborator who navigates matrixed organizational dynamics, working seamlessly with Legal/Risk/Compliance, Technology/Engineering, and business teams to establish AI principles, governance playbooks, and technical roadmaps
• A clear communicator who can translate AI governance concepts and technical risk findings into language that resonates with non-technical stakeholders and leadership
• A proactive problem-solver who thrives on staying ahead of AI governance expectations and emerging regulations — and can turn frameworks into practical controls
• An adaptive contributor who embraces the pace of consulting, working across diverse sectors and practice areas

The annual salary for this role ranges from: $160,000 to $175,000 + benefits. This role is also eligible for bonuses, based on individual and company performance. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to, geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity. 

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.  We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or ​expression, veteran status, or any other status protected under federal, state, or local law.

Please note that as per Accordion policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.

#LI-HA1

Please note: This position is not eligible for immigration sponsorship. 

Company Overview 

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation. 

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark.  

AI Governance Team, AI Risk and Operations 

We are seeking a Vice President, AI Risk and Operations on our AI Governance Team who will play a critical role in maturing and scaling Accordion's enterprise-wide AI Governance risk and operations program. In this role, you will serve as an internal governance practitioner and cross-functional advisor, embedding AI governance policies, procedures, and controls across our operating model for internal AI solutions — with the expectation that this scope will evolve to include client-facing engagements over time. Drawing on your experience with AI policy, frameworks, and risk program design, you will translate complex governance requirements into actionable, scalable implementation systems. This position requires seamlessly bridging the gap between cutting-edge AI development and responsible governance, partnering with senior stakeholders across Practices, Technology, Legal, and Emerging Technology to enabling trusted use and development of AI.  

This position can be based in our New York City or Chicago offices and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location. 

This position is not eligible for immigration sponsorship. 

What You’ll Do 

Governance & Frameworks 

• Enhance the enterprise AI Risk Management Framework, including AI use case and supply chain inventory management, use case risk classification taxonomies, and risk-tiering mechanisms aligned to internal standards and emerging regulatory expectations 
• Design and operationalize scalable, end-to-end governance processes across the AI lifecycle  
• Build and maintain AI governance playbooks, risk appetite frameworks, and responsible AI standards  
• Identify opportunities to strengthen controls and oversight through process automation, tooling improvements, and governance workflow optimization 

Cross-Functional Collaboration 

• Partner with Legal, Technology, and Consulting Practice Groups to embed explainability, bias mitigation, and ethical AI principles directly into use case development and delivery workflows 
• Manage the firm's AI Governance obligations and processes end-to-end, including supporting AI and related vendor management supply chain   
• Coordinate with Legal teams to ensure AI systems meet applicable jurisdictional and regulatory requirements, including proactive engagement on evolving global AI legislation 
• Facilitate stakeholder working groups, cross-functional governance forums, and executive communications on AI risk priorities, testing outcomes, and documentation requirements 
• Maintain the internal AI risk register and escalate issues through appropriate governance channels 
• Liaise with Technology and Practices to ensure data lineage and quality standards are met for AI solutions 

Monitoring & Oversight 

• Establish, track, and report on key risk indicators (KRIs) for AI systems in partnership with the Responsible AI Data Scientist and AI Governance Lead, across internal and client-facing AI solutions and products 
• Monitor alignment with global AI regulatory frameworks (e.g., EU AI Act, NIST AI RMF) and support responses to regulatory inquiries, audits, or reviews 
• Evaluate risks associated with third-party and vendor AI solutions across the full sourcing lifecycle — including procurement, onboarding, integration, and ongoing performance oversight — and identify operational guardrails and controls 
• Assess design and operating effectiveness of AI controls against internal policy and external standards, especially for AI, privacy, and industry regulations, under Legal's guidance 
• Produce high-quality audit findings reports with clear recommendations for remediation and monitor implementation of agreed action plans 
• Stay current on AI regulation, industry standards, and emerging best practices 

Internal Enablement (Evolving) 

• Support the development of AI Governance updates, training/awareness programs, and culture-building initiatives to embed responsible AI practices across the organization 
• Contribute to Accordion's Trustworthy AI methodology and internal IP development 
• Over time, support client-facing AI governance assessments, risk remediation roadmaps, and responsible AI frameworks as the program matures and scope expands  

You Have 

• Bachelors degree in Finance, Business Administration, or related field  
• 7+ years’ experience in Risk Operations, Privacy Programs, or PMO/IMO, with at least 3 years directly focused on AI governance or oversight - preferably within professional services, consulting, or PE-backed environments. 
• Demonstrated experience leading complex, multi-jurisdictional integrations and/or global expansion programs, with a track record of building and running structured governance. 
• Strong knowledge of AI and privacy regulations and standards — including EU AI Act, NIST AI RMF, GDPR, CCPA, and ISO 42001 — and the ability to translate regulatory mandates into operational controls 
• Strong grasp of AI/ML technical risks (e.g., bias, model drift, robustness) and associated controls 
• Strong familiarity with regulatory and operational considerations relevant to cross-border professional services (e.g., data/privacy, employment, tax, licensing), and the ability to operationalize them into business processes. 
• Exceptional communication skills with the ability to convey complex technical and regulatory considerations to non-technical stakeholders, including leadership and cross-functional teams 
• Comfortable operating in a high-growth, entrepreneurial environment, with a bias toward structure, scalability, and execution discipline. 
• Strong analytical and problem-solving skills  
• AI usage and familiarity required 
• Excellent attention to detail and organizational skills   
• Ability to adapt to changing priorities and work effectively in a dynamic environment   

Preferred Qualifications 

• Experience in Data Risk Management or direct collaboration with AI/ML development teams 
• Familiarity with AI risk management platforms or tools for model monitoring, documentation, and compliance reporting 
• Experience designing training, awareness, or enablement programs focused on AI risk, model governance, or responsible AI practices 
• Certifications in risk, privacy, or compliance (e.g., CIPP, CIPM, CRISC, CRCM) 
• Passion for AI and a desire to build a world-class risk management function  

You Are 

• Energized by building and scaling governance programs that make AI deployment safer, more trustworthy, and more compliant — across a dynamic, fast-moving consulting environment 
• A cross-functional collaborator who navigates matrixed organizational dynamics, working seamlessly with Legal/Risk/Compliance, Technology/Engineering, and business teams — and can drive decision making and ownership across diverse stakeholders 
• A clear communicator who can translate AI governance concepts, regulatory requirements, and risk findings into actionable guidance for business, technical, and executive audiences 
• A proactive problem-solver who thrives on staying ahead of AI governance expectations and emerging regulations, and can turn frameworks into operational reality 
• An adaptive contributor who embraces the breadth and pace of consulting, working across diverse sectors and practice areas 

The annual salary for this role ranges from: $130,500 to $145,000 + benefits. This role is also eligible for bonuses, based on individual and company performance. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to, geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity.  

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.  We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or ​expression, veteran status, or any other status protected under federal, state, or local law. 

Please note that as per Accordion policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity. 

#LI-HA1

The Technology, Data, and Intelligence Team 

Okta is the leading independent identity provider. The Technology, Data, and Intelligence (TDI) organization is the engine that powers Okta's global workforce, providing the technology and systems that enable our employees to do their best work.

The Staff Data Scientist Opportunity

We are looking for a Staff Product Data Scientist to join our Data & Insights team. This role will lead the strategy, development, and operationalization of advanced analytics and machine learning solutions that power data intelligence for Okta’s Product Management teams, uncovering actionable insights on customer behavior, product engagement, and opportunities that will drive our product growth strategy. You’ll define the long-term data science roadmap while partnering closely with Okta’s diverse Product Management teams and executive leadership.

What you’ll be doing 

• Strategic Product Influence: Collaborate closely with Product Managers and leadership to provide insights that will help drive product strategy and roadmaps, ensuring decisions are grounded in a data-driven approach.
• Advanced Analytics and Modeling: Build and deploy statistical and machine learning models (e.g., predicting churn, lifetime value, feature adoption) to forecast user behavior and product growth opportunities in order to help influence roadmap decisions.
• Deep-Dive Insight Generation: Conduct thorough exploratory analysis on extensive, complex datasets to uncover key drivers of user adoption and engagement, identifying unseen opportunities for significant product improvement.
• Data Ecosystem Partnership: Work with data engineering, analytics engineering, and data analysts to shape and enhance the foundational data infrastructure necessary for scalable ML and advanced analytics initiatives.
• Data Preparation and Curation: Develop and construct usable data sets by integrating and manipulating information from various disparate data sources as needed.
• Executive Communication and Influence: Translate intricate data insights into clear, compelling narratives for executives, product managers, and engineers, effectively influencing crucial business and product decisions.

What you’ll bring to the role

• 7+ years of experience in data science or ML, including 3–5 years in a senior, staff, or technical leadership role.
• Deep understanding of product analytics and data science frameworks, with a proven history of designing and analyzing product data to solve complex, ambiguous business problems and deliver measurable results.
• Demonstrated ability to apply cutting-edge AI tools to accelerate the discovery of deep, actionable insights from complex product data.
• Demonstrated ability to translate data insights into product impact and formulate strategic, data-driven recommendations.
• Deep expertise in machine learning algorithms (supervised, unsupervised, NLP, forecasting, optimization) and statistical modeling.
• Strong proficiency in Python, SQL, and leading ML libraries.
• Excellent communication skills and a proven ability to influence Product and executive partners.

And extra credit if you have experience in any of the following! 

• Experience in high-growth SaaS, cybersecurity, identity, or enterprise software environments.
• Prior ownership of ML platform/tooling decisions and evaluations.
• Experience enabling self-service analytics or citizen data science capabilities.

#LI-MC1

#LI-Hybrid

#P23809_3392886

The Pricing Strategy Team
Okta’s Pricing Strategy team partners across Product, Finance, Sales, and Operations to shape how we package, price, and monetize our portfolio globally. We sit at the intersection of strategy and analytics, translating market signals and customer behavior into clear recommendations that drive growth and value capture. The team’s work is highly cross-functional and directly influences executive decision-making and field execution.

The Principal Data Scientist, Pricing Strategy Opportunity
Reporting to the Head of Pricing Strategy, this role will lead the data science and analytics strategy that underpins portfolio-level pricing and packaging decisions. You’ll combine strong quantitative rigor with strategic thinking to design measurement approaches, build and operationalize models, and run test-and-learn pilots that inform high-impact monetization programs. You will partner closely with senior leaders across Product and GTM to turn ambiguous questions into actionable insights, recommendations, and scalable execution plans.

What you’ll be doing

• Strategic Pricing Influence: Partner with Product, GTM, and Finance leadership to inform portfolio-level pricing, packaging, and discount strategy with data-driven recommendations
• Advanced Analytics and Modeling: Build and operationalize models and analytical frameworks to forecast pricing impact, customer behavior, and revenue outcomes across segments and geographies
• Experimentation and Pilots: Design and evaluate pilots and test-and-learn programs for new pricing initiatives, defining success criteria and measurement plans
• Deep-Dive Insight Generation: Analyze large, complex datasets to uncover drivers of purchasing, discounting, retention, and monetization performance
• Metrics and Dashboard Development: Establish the right KPIs and build dashboards to monitor monetization strategy effectiveness and the ROI of pricing initiatives in real time
• Data Foundation Partnership: Work with Okta Data teams to shape and enhance the foundational data required for pricing analytics initiatives
• Cross-Functional Execution Partnership: Translate strategy and insights into operational requirements, working with stakeholders across Sales, Legal, and Systems teams to enable implementation and adoption

What you’ll bring to the role

• 8+ years of experience in data science, analytics, pricing, strategy consulting, or a related quantitative field (B2B SaaS preferred)
• Proven ability to apply statistical rigor and structured analytics to ambiguous business problems and deliver measurable impact
• Experience designing measurement approaches for business initiatives (e.g., pilots, rollouts, test-and-learn), and communicating results with clarity
• Strong proficiency in SQL and Python, with experience working in modern data environments (e.g., Snowflake) and BI tools (e.g., Tableau)
• Ability to synthesize complex data using quantitative approaches, translate findings into clear visualizations, and deliver executive-ready insights and recommendations
• Demonstrated ability to influence cross-functional senior stakeholders and lead through ambiguity with strong collaboration and ownership

And extra credit if you have experience in any of the following!

• Experience in pricing, packaging, monetization, or growth strategy for multi-product SaaS portfolios
• Familiarity with forecasting, optimization, or causal measurement methods in a business context
• Experience partnering with Sales/GTM teams to drive adoption of new programs and measure field impact

#LI-MC1

#LI-Hybrid

#P17449_3411893

As a member of the Data Science & Analytics team, you will help Discord achieve its mission of making it easier and more fun for people to talk and hang out before, during, and after playing games. Senior Data Scientists for Analytics leverage their deep analytical skills and product intuition to solve a wide array of complex problems - from strategic analysis to dashboard creation and experimentation design and analysis. We are currently hiring across a variety of data science verticals and teams. If you’re passionate about data, impact, and working on an amazing team, read on!

What you'll be doing

• Partner with teams throughout Discord through the full lifecycle of data science analytics from ideation and exploratory analysis, to building dashboards and reports, and A/B testing
• Define KPIs and metrics that help improve the user experience, encapsulating these measures in clean crisp dashboards that provide the company with timely and actionable information
• Use our amazing infrastructure to quickly and easily build custom data sets to monitor novel product features and processes
• Proactively socialize insights, dashboards, and reports with technical and non-technical audiences, soliciting feedback on where to improve
• Be a champion of A/B testing and help groups throughout the company design, analyze, and interpret A/B tests correctly
• Collaborate with data and engineering teams to design scalable and future-proof instrumentation

What you should have

• 4+ years of experience autonomously translating ambiguous business problems into deep informative insights through hands-on analytics
• 4+ years of experience building performant dashboards using Tableau, Looker, or similar software - with proficiency in designing clean crisp visualizations
• 4+ years experience writing excellent SQL
• Excellent communication skills, with the ability to translate complicated findings or technical approaches in easy-to-understand ways
• 4+ years of experience in the design, analysis, and interpretation of A/B tests in a large data environment
• A desire to work with amazing, passionate people who care deeply about solving challenging problems to improve Discord
• Last but not least - a collaborative attitude and a healthy dose of natural curiosity!

Bonus Points

• Passion for Discord or online communities
• Experience with technical leadership, being the point person for one or more stakeholder groups
• Experience with analytics for social media or international subscription-based online services, including familiarity with concepts such as social graphs, LTV analysis, funnel analysis, etc.
• Experience in the user engagement and growth problems
• Experience writing performant code in BigQuery SQL
• Experience with writing production ETL

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

As a member of the Data Science & Analytics team, you will help Discord achieve its mission of making it easier and more fun for people to talk and hang out before, during, and after playing games. Data Scientists for Analytics leverage their deep analytical skills and product intuition to solve a wide array of complex problems - from strategic analysis to dashboard creation and experimentation design and analysis. We are currently hiring across a variety of data science verticals and teams including revenue and performance. If you’re passionate about data, impact, and working on an amazing team, read on!

What you'll be doing

• Partner with teams throughout Discord through the full lifecycle of data science analytics from ideation and exploratory analysis, to building dashboards and reports, and A/B testing
• Define KPIs and metrics that help improve the user experience, encapsulating these measures in clean crisp dashboards that provide the company with timely and actionable information
• Use our amazing infrastructure to quickly and easily build custom data sets to monitor novel product features and processes
• Proactively socialize insights, dashboards, and reports with technical and non-technical audiences, soliciting feedback on where to improve
• Be a champion of A/B testing and help groups throughout the company design, analyze, and interpret A/B tests correctly
• Collaborate with data and engineering teams to design scalable and future-proof instrumentation

What you should have

• 3+ years of experience autonomously translating ambiguous business problems into deep informative insights through hands-on analytics
• 3+ years of experience building performant dashboards using Tableau, Looker, or similar software - with proficiency in designing clean crisp visualizations
• 2+ years experience writing excellent SQL
• Excellent communication skills, with the ability to translate complicated findings or technical approaches in easy-to-understand ways
• 2+ years of experience in the design, analysis, and interpretation of A/B tests in a large data environment
• A desire to work with amazing, passionate people who care deeply about solving challenging problems to improve Discord
• Last but not least - a collaborative attitude and a healthy dose of natural curiosity!

Bonus Points

• Passion for Discord or online communities
• Experience with analytics for social media or international subscription-based online services, including familiarity with concepts such as social graphs, LTV analysis, funnel analysis, etc.
• Experience in the user engagement and growth problems
• Experience writing performant code in BigQuery SQL
• Experience with writing production ETL
• Experience leveraging AI for data science

The US base salary range for this full-time position is $160,000 to $180,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Small business owners trust Gusto with something fundamental: making sure their people get paid, on time, every time. As a Principal Data Scientist on the Payments team, you'll sit at the intersection of financial infrastructure and data science — translating the complexity of a high-scale payments ecosystem into the insights and models that shape how we build, operate, and improve our payments products. 

In this role you will work closely with our Product, Engineering, Design, Finance, and other Data teams to become an expert in the data for your domain, define and track metrics that help us understand our business performance, and dive deep into our payments data to deliver insights and answer questions. You’ll also integrate AI-assisted practices to accelerate analysis, enhance rigor, and expand the reach of insights across Gusto. 

This is a role for someone who's equally comfortable diving into ledger-level transaction data and standing in front of a payments engineering team to influence architecture decisions. If you want your work to directly protect and improve the financial lives of hundreds of thousands of small businesses, this is the role.

Here’s what you’ll do day-to-day:

• Own payments intelligence end-to-end: Design and maintain measurement frameworks for payment success rates, failure root causes, retry strategies, and settlement timing — becoming the authoritative source of truth for payments health across the org.
• Partner with payments engineering: Embed with backend engineering teams to understand infrastructure constraints and data availability, translate that knowledge into well-scoped experiments, and influence roadmap prioritization with data-backed recommendations.
• Drive experimentation at scale: Design and analyze A/B tests and quasi-experiments across payment flows — including retry logic, routing decisions, and failure recovery — ensuring statistical rigor even in low-conversion, high-variance payment environments.
• Build predictive models: Develop and deploy models for payment failure prediction, risk scoring, and anomaly detection that operate at Gusto's transaction volume, partnering with Machine Learning Engineers and Product Engineers on productionization and monitoring.
• Build AI-native data products: Go beyond using AI to go faster; build data products and automated workflows with AI as a core component. Know what "good" looks like for a clustering model or automated workflow, when to trust the output, when to challenge it, and how to build guardrails that let the team scale AI use responsibly in a regulated financial context.
• Own the business narrative: Be the person payments product and engineering leadership calls before an exec review, not after. Comfortable defending methodology on ARR projections, CX attribution, and cost savings in a room with skeptics. Translate nuanced statistical results and model outputs into clear, actionable narratives for payments engineers, product managers, finance partners, and executive leadership.

Here’s what we're looking for:

• 10+ years of experience in Data Science or a closely related quantitative role at a product-focused software company, with meaningful exposure to payments, fintech, or financial infrastructure.
• Deep payments domain knowledge: Hands-on experience with payments infrastructure: ACH, card networks, bank integrations, settlement flows, or equivalent, with a strong intuition for how backend systems shape data availability and quality.
• Strong SQL and Python skills, with experience querying large-scale transactional datasets and building reproducible analytical pipelines.
• Proven experimentation and causal inference expertise: Ability to design rigorous experiments in challenging payment contexts (rare events, high variance, non-stationarity) and communicate trade-offs clearly.
• AI-native mindset: Has built data products and analytical workflows with AI as a core component, not just used AI to go faster. Knows what "good" looks like for a clustering model or automated workflow, when to trust the output, when to challenge it, and how to build guardrails that scale AI use responsibly in a financial context.
• Cross-functional influence: Track record of collaborating with and influencing backend engineers and technical stakeholders, not just product and business partners.

Our cash compensation amount for this role is targeted at $184,000/yr - $210,000/yr in Denver, and $217,000/yr - $250,000 for San Francisco and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Description

Reporting to the SVP of Research, the Senior Scientist I, Medicinal Chemistry will bring deep expertise in medicinal chemistry and will play a key role in advancing a pipeline of novel therapeutics enabled by integrin biology and targeted delivery strategies. This role will lead the design and optimization of drug candidates that leverage integrin-mediated delivery to selectively target tissues and cell types.

Responsibilities

• Design and drive medicinal chemistry strategies for integrin-targeted therapeutics and delivery-enabled small molecules
• Utilize Structure-Activity Relationships to prioritize hypotheses, set design criteria, and guide external synthesis efforts
• Evaluate and interpret complex datasets and translate findings into clear, actionable design decisions
• Collaborate closely with biology, structural biology, DMPK, and translational teams to integrate insights into compound design and program strategy
• Prioritize and manage multiple tasks to ensure timelines and deliverables are met
• Maintain high-quality documentation and data management practices
• Present data and strategy clearly to internal teams and senior leadership
• Contribute to intellectual property strategy and filings
• Foster a collaborative, innovative, and high-performance research culture

Qualifications

To perform this job successfully, an individual must be able to perform each essential duty. The requirements listed below are representative of the knowledge, skill, abilities, and prior experience required.

• PhD in Organic Chemistry or a related discipline
• 4+ years of relevant industry experience
• Strong foundation in synthetic organic chemistry and medicinal chemistry, with demonstrated ability to guide compound design, interpret SAR, and apply physicochemical and structural insights leading to optimized drug candidates
• Proven ability to work effectively on multidisciplinary teams in a fast-paced research environment
• Demonstrated track record of progressing compounds towards development
• Exceptional organizational and project management skills, with the ability to manage competing priorities
• Excellent written and verbal communication skills

  Preferred Qualifications

• Experience with antibody-drug conjugates (ADCs), linker-payload systems, or other targeted delivery modalities
• Demonstrated ability to integrate biology-driven insights into chemistry strategy, including payload selection and receptor-mediated uptake strategies
• Track record of meaningful contributions to candidate selection

How you work

• Dare to Succeed: Brings intellectual curiosity and scientific courage to challenge conventional approaches and explore innovative chemistry and delivery strategies. Pursues bold yet data-driven solutions to advance integrin-enabled therapeutics.
• Make an Impact: Takes strong ownership of scientific outcomes, proactively driving decisions and progress with urgency and accountability. Translates complex data into clear actions that move programs efficiently toward development.
• One Pliant: Works collaboratively across disciplines, valuing diverse perspectives to strengthen scientific decisions. Aligns individual contributions with team and company goals to drive collective success.

The annual base salary for this role is $160,000 – $180,000. Individual pay may vary based on additional factors, including, and without limitation job-related skills, experience, work location and relevant education or training. Pliant’s compensation package also includes benefits, equity, and annual target bonus for fulltime positions.

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale Generative AI experiences — including Pinterest Assistant and Canvas — ensuring these products are safe, fair, and trustworthy is paramount. We are looking for a Senior Data Scientist to help lead Pinterest's responsible AI mandate within the Advanced Technology Group (ATG). In this role, you will design and build the data science foundations for automated adversarial testing of our GenAI products — developing attack strategies, evaluation frameworks, and harm-detection methodologies that operate at scale. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Trust & Safety specialists, Policy teams, and Product Managers. You are expected to develop a deep understanding of generative AI vulnerabilities, and generate insights and robust methodologies to proactively surface and mitigate risks. The results of your work will directly influence product safety, policy compliance, and user trust across Pinterest.

What you'll do

• Design and develop automated adversarial testing methodologies — including single-turn, multi-turn, and multimodal attack strategies — to proactively identify vulnerabilities in Pinterest's Generative AI products.
• Build and calibrate hybrid evaluation pipelines combining LLM-based judges, classifiers, and rule-based systems to accurately detect safety violations, policy breaches, bias, and representational harms.
• Develop and operationalize harm taxonomies grounded in industry standards and Pinterest's Responsible AI and Trust & Safety threat models.
• Design adaptive refinement loops that learn from attack outcomes (near-misses, partial failures) to iteratively surface deeper and previously unknown vulnerabilities.
• Bring scientific rigor and statistical methods to the evaluation of AI safety — including benchmark dataset construction, evaluation calibration, and success-metric definition (vulnerability severity, coverage breadth, pre-launch risk reduction).
• Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML engineers, Trust & Safety specialists, policy teams, product managers, and legal partners to ensure safe product launches.
• Relentlessly focus on impact, whether through influencing product safety strategy, advancing responsible AI metrics, or improving critical evaluation processes.
• Mentor and up-level junior data scientists and cross-functional partners on adversarial evaluation, responsible AI methodologies, and safety-aware data science practices.

What we're looking for

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Strong interest and hands-on experience in one or more of: AI safety, adversarial machine learning, red teaming, responsible AI, or trust & safety.
• Deep familiarity with large language models (LLMs), generative AI systems, and their failure modes — including prompt injection, jailbreaks, bias, and safety violations.
• Experience designing and calibrating evaluation frameworks for AI systems — including LLM-as-judge, classifier-based evaluation, and benchmark dataset construction.
• Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines and large-scale experimentation.
• Familiarity with AI safety taxonomies and frameworks (e.g., OWASP LLM Top 10, MITRE ATLAS) is strongly preferred.
• Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership.
• Excellent written and verbal communication skills, with the ability to explain complex technical findings to both technical and non-technical partners.
• A team player eager to partner across Responsible AI, Trust & Safety, Product, Engineering, Policy, and Legal to turn safety insights into action.

This position is not eligible for relocation assistance.

#LI-NM4 

Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale and unify our foundational AI models across every recommendation surface, rigorously measuring the system-level impact of these advances is essential to our ability to ship with confidence and compound gains over time.

We are looking for a Senior Data Scientist to serve as the measurement backbone for Pinterest's foundational model initiatives within the Advanced Technology Group (ATG). In this role, you will design the evaluation frameworks, experimentation strategies, and system-level metrics that quantify how improvements to our largest and most complex models translate into real user and business outcomes. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Applied Scientists, Product Managers, and ML Platform engineers. 

You are expected to develop a deep understanding of Pinterest's recommendation ecosystem, from representation learning to retrieval, ranking, reinforcement learning, and beyond, and bring the analytical rigor necessary to decompose, attribute, and communicate the impact of foundational model changes across this interconnected system. The results of your work will directly influence model investment decisions, launch criteria, and the pace of innovation across ATG and Pinterest.

What You'll Do

• Design and execute system-level measurement frameworks for foundational model improvements spanning offline evaluation benchmarks, online A/B experiments, and longitudinal impact tracking across surfaces.
• Define, and own the success metrics that quantify foundational model value.
• Build causal inference methodologies to isolate the incremental impact of individual model components within a complex, multi-model production system where changes co-occur and interact.
• Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML Engineers, Applied Scientists, Homefeed and Surface teams to ensure measurement rigor is embedded in every model launch.
• Relentlessly focus on impact, whether through sharpening investment decisions with data, raising the bar for launch criteria, accelerating experimentation velocity, or surfacing hidden inefficiencies in the model ecosystem.

What We're Looking For

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Strong interest and hands-on experience in one or more of: ML system evaluation, recommender system measurement, A/B experimentation at scale, causal inference
• Deep familiarity with large-scale recommendation or ranking systems and their evaluation including an understanding of how representation learning, retrieval, ranking, and re-ranking stages interact and compound in production.
• Experience designing and executing A/B experiments for complex ML systems,  including multi-surface holdouts, metric decomposition, long-run effect estimation, and interference/spillover mitigation.
• Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines, feature stores, and large-scale experimentation platforms.
• Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership in a fast-moving research-to-production environment.
• Excellent written and verbal communication skills, with the ability to translate complex system-level findings into clear narratives for technical and non-technical partners including leadership-level investment recommendations.
• A team player eager to partner across teams to turn measurement insights into better models and faster launches.

This position is not eligible for relocation assistance.

#LI-NM4

The Opportunity:

Grow Therapy is seeking a Staff Data Scientist to deepen our understanding of our users and unlock the next era of our growth trajectory. In this role, you will lead cross-functional, data-driven initiatives and drive insights that get more people successfully onboarded and retained in online therapy, shape how we build our mobile app and digital experiences, and lead the charge on how AI is used alongside therapy. You will also develop and own marketing and attribution models that help us reach patients more effectively and empower our providers’ success. Your work will shape product strategy, experimentation, and long-term investment decisions across the company.

What You’ll Be Doing:

• Lead experimentation and metric development to understand user behavior, optimize onboarding and retention, and guide product direction across web and mobile experiences.
• Build predictive, attribution, and behavioral models that inform marketing strategy, therapist-matching workflows, and future AI-powered features.
• Partner closely with Product, Engineering, Design, and Operations to identify opportunities, quantify impact, and drive roadmap decisions with clear, actionable insights.
• Develop dashboards, analytical frameworks, and self-serve tools that scale data access and empower teams to answer their own product questions.
• Shape Grow Therapy’s AI strategy by designing evaluation frameworks, running model-level experiments, and identifying where AI can improve the patient and provider experience.

You’ll Be a Good Fit If:

• 8+ years of experience in a quantitative role applying analytics, experimentation, and modeling in a product-focused environment, including leading high-impact, cross-functional data science or analytics initiatives.
• Fluent in SQL and Python, with deep experience designing A/B tests, building models, and setting a high bar for translating complex data into clear recommendations for stakeholders at all levels.
• Proven experience owning and driving product or growth decisions through deep user understanding, funnel analytics, or marketplace dynamics, and doing so through influence as well as hands-on work.
• Comfortable navigating ambiguity and working cross-functionally in fast-moving environments where data science directly influences strategy, and aligning multiple teams around shared metrics and insights.
• Excited about improving access to mental health care and motivated by building AI-enhanced experiences that support therapists and patients.

Role Details:

Employment Type: Full Time, Exempt
Base Compensation: The base compensation range for this position is:

• Hybrid Commitment: $200,000–$250,000 USD USD Annually

This role can be hybrid (onsite from our NYC, San Francisco, or Seattle hub location three days per week: Tuesday, Wednesday, Thursday) or fully remote. Both arrangements include travel 2–3 times per year (e.g., company and department off-sites).