Data Scientist, B2B Demand Generation, Growth & Measurement

About the Role OpenAI's ads business is scaling quickly. As the Data Scientist for Ads Demand, you will build the measurement and insight foundation for understanding demand health and advertiser value across the marketplace. You will partner closely with Ads Sales leadership and Ads Product leadership—along with Marketing Science and product and sales teams—to diagnose advertiser performance, define benchmarks, identify growth opportunities, and turn advertiser feedback into product priorities. Your work will shape demand strategy, improve advertiser outcomes, and help OpenAI build for its most valuable advertisers. What You'll Do Demand Health & Measurement Define the North Star metrics, diagnostic framework, and measurement strategy for demand health across the ads system. Build the operating view of demand across spend, active advertisers, retention, budget utilization, delivery, concentration, and mix; identify emerging risks and opportunities. Diagnose changes in demand through cohort analysis, decomposition, experimentation, and causal methods, translating findings into clear actions for Sales and Product leadership. Advertiser Performance & Benchmarks Own the end-to-end view of advertiser outcomes—including delivery, ROAS, conversion performance, retention, and budget efficiency—for individual advertisers and key cohorts. Establish actionable benchmarks by objective, vertical, advertiser size, geography, maturity, and product adoption, with statistically sound peer comparisons. Develop early-warning signals and opportunity scoring that help sales teams surface under-delivery, performance risk, and advertiser growth potential. Set standards for metric definitions, data quality, and interpretation so leaders can separate real marketplace changes from seasonality, selection effects, and measurement artifacts. Insights, Adoption & Advertiser Feedback Partner with Marketing Science, Sales, and Product to translate analysis into credible advertiser-fac

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

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 Product Data Scientist to establish how product decisions at Baseten are made with data. You'll work directly with Product and Engineering, alongside GTM to determine measurement, strategy, experimentation and implementation. This is a foundational, hands-on role. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape product strategy. You'll work from clickstream and product events through inference telemetry and observability data, helping Baseten make faster decisions about reliability, performance, adoption and developer experience. RESPONSIBILITIES Partner directly with Product and Engineering: frame the questions that matter, define success criteria, and turn analysis into roadmap, launch, and prioritization decisions. Define how product success is measured: establish metrics across activation, adoption, retention, expansion, reliability and user experience. Support experimentation and launches: design measurement plans, analyze A/B experiments and controlled rollouts, and translate results into product decisions. Diagnose reliability and scaling behavior: join customer signals with request, replica, deployment, and cluster telemetry to find patterns in release bottlenecks, unhealthy replicas, and models without traffic. Define the enterprise customer journey and measure feature adoption

About the Role OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering. What You'll Do Full-Funnel Analytics Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention. Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations. Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders. Targeting, Segmentation & Propensity Modeling Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers. Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking. Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels. Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth. Campaign Analytics & Measurement Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy. Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership. Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews. Forecasting & Planning Build high-fidelity revenue and advertiser growth models to project perfor

About the team OpenAI’s Education team is building products and experiences that help learners, educators, and institutions benefit from AI in ways that are rigorous, useful, and grounded in real learning outcomes. The work spans both consumer and B2B education, with close collaboration across engineering, learning science, design, data, and research. This team sits in a highly strategic investment area for OpenAI, with strong opportunities to shape how product ideas flow across consumer and institution-facing experiences. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the role We’re looking for a product-minded Full Stack Engineer to help build OpenAI’s education products from the ground up. You’ll own end-to-end development across the stack, from early concepting and prototyping through production launch and iteration. This is an opportunity to work on a highly strategic, early-stage product area where engineering judgment, product sense, and customer empathy all matter. You’ll partner closely with leaders across the education org, including learning scientists, researchers, designers, and cross-functional partners, to turn emerging ideas into durable product experiences for schools, universities, and other education stakeholders. In this role, you will: Build and ship product experiences across the full stack for OpenAI’s education offerings Own projects end-to-end, from ideation and technical design through implementation, launch, and iteration Work closely with learning scientists and researchers to translate learning goals and evidence into product decisions Collaborate with design, data, and cross-functional partners to build thoughtful, high-quality user experiences Help define the engineering foundation for a growing education pod, including patterns, systems, and technical

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