Data Scientist

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Scientist to help build and scale our internal analytics capabilities. This is a foundational role where you’ll create dashboards, models and insights to power business and product teams alike. You’ll collect requirements, define key metrics, and deliver recommendations directly to stakeholders. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape Baseten’s product and strategy. RESPONSIBILITIES Build and maintain production-grade models and dashboards across multiple functions with a focus on accuracy, simplicity and user experience. Define and instrument core metrics around capacity, availability, ROI, product adoption, revenue and costs. Ingest and transform raw data using tools like dbt, Airbyte, and Databricks. Partner with Engineering, Finance, Marketing, and Sales teams to understand goals and translate them into data solutions Analyze product, operational and commercial data to identify opportunities, quantify tradeoffs, and influence product and GTM priorities. Present findings and recommendations to technical and nontechnical audiences, including company leaders. REQUIREMENTS 5+ years of experience in analytics, BI, or data engineering roles Strong SQL skills with the ability to write complex queries for data transformation and analysis Experience designing medallion data arch

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Senior Data Scientist - Network Value (Credit) The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Data Scientist supporting Credit, a critical product area within Plaid’s Network Value portfolio. You’ll become a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders, helping shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and KPIs tied to business goals and user experiences, a

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview We’re hiring a Marketing Data Scientist to partner closely with Harvey’s Marketing organization and build our marketing data science function from the ground up. In this role, you’ll serve as a trusted analytical partner to Marketing, GTM, and Finance - defining how we measure marketing success, understanding what drives channel and campaign performance, and informing where and how we invest to accelerate growth. As one of the earliest Marketing data science hires, you’ll own the development of core Marketing metrics, scalable dashboards, and analytical frameworks that enable data-driven decision-making across the business. What You’ll Do Embed deeply with the Marketing organization as a trusted partner, identifying opportunities to improve performance and drive growth

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function. You will partner with Product, Engineering, Design, Go-to-Market, and company leadership to define how we measure product success, understand user behavior, and make high-quality decisions in a fast-moving environment. This role is both strategic and hands-on. You will define north-star and product-level metrics, design experiments and causal analyses, build source-of-truth reporting, and turn ambiguous product questions into clear recommendations. You should be comfortable operating where the data is imperfect, the product is evolving quickly, and the right answer requires both analytical rigor and strong

About the Role We are hiring a Data Scientist to help build OpenAI's B2B ecosystem and go-to-market data science capability. You will turn ambiguous commercial questions into evidence, recommendations, and operating decisions that help OpenAI understand where to focus as our B2B business expands. OpenAI's B2B motion is growing quickly across products, customer segments, markets, and field teams. This role will partner with leaders across GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science to answer questions tied to international strategy, monetization, product penetration, field deployment, customer opportunity, and organizational design. This is a founding-style opportunity within the broader GTM Data Science organization. The team and stakeholder model are still evolving, so you should be energized by building structure in ambiguity, helping define how the team works, and helping shape the bench around a high-priority commercial area. In this role, you will bring data science craft, consulting-style problem solving, practical AI fluency, and strong business judgment to help senior leaders make better B2B decisions. In this role, you will: Structure ambiguous B2B and go-to-market questions into clear operational plans, identifying the decision at stake, the evidence needed, and how insights will translate into action. Lead strategic deep dives across international expansion, monetization, product penetration, customer segmentation, field deployment, ecosystem dynamics, and organizational design. Analyze product usage, customer behavior, adoption patterns, sales and field activity, pipeline and revenue signals, and market context to identify the drivers of B2B growth. Partner closely with GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science leaders to turn analysis into prioritization decisions, field plays, investment choices, and operating cadences. Communicate complex findings to executives and cross-functional partners with crisp re

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We operate at the intersection of Product, Engineering, Risk, Finance, and Go-to-Market to ensure that paying for OpenAI products is seamless, reliable, scalable, and globally optimized. As OpenAI expands internationally and across product surfaces, FinEng plays a critical role in enabling durable, efficient revenue growth. About the Role As a Data Scientist for Financial Engineering, you will drive the measurement, experimentation, and optimization work that powers OpenAI’s monetization infrastructure. You will define how we measure and improve checkout, payments, subscriptions, and pricing systems globally—balancing conversion, risk, cost, reliability, and user experience. As a senior individual contributor, you will establish source-of-truth metrics, design rigorous experiments, develop analytical frameworks, and translate complex findings into decisions that directly affect revenue and international growth. This role is based in San Francisco, CA. We use a hybrid model of three days per week in the office and offer relocation support. In this role, you will Define key metrics and guardrails across checkout, payments, subscriptions, and pricing. Design experiments, staged rollouts, and offline incrementality studies. Improve conversion, payment performance, retention, and involuntary churn. Develop pricing, elasticity, FX, and localization frameworks. Partner with Data Engineering to build trusted datasets and operational monitoring. Turn complex analysis into recommendations that shape product and business decisions. Provide technical leadership and mentor other data scientists. You might thrive in this role if you have 10+ years of experience in data science, experimentation, or product analytics. Experience with monetization, payments, checkout, subscr