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OpenAI is hiring a Data Scientist for its rapidly scaling ads business. You will build the measurement and insight foundation for understanding demand health and advertiser value across the marketplace, partnering closely with Ads Sales, Ads Product, Marketing Science, and product and sales teams.
Key responsibilities include:
**Demand Health & Measurement**: Define North Star metrics, diagnostic frameworks, and measurement strategy for demand health. Build an operating view of demand across spend, active advertisers, retention, budget utilization, delivery, concentration, and mix. Diagnose changes through cohort analysis, decomposition, experimentation, and causal methods, translating findings into clear actions for leadership.
**Advertiser Performance & Benchmarks**: Own the end-to-end view of advertiser outcomes including delivery, ROAS, conversion performance, retention, and budget efficiency. Establish actionable benchmarks by objective, vertical, advertiser size, geography, maturity, and product adoption. Develop early-warning signals and opportunity scoring to help sales teams surface under-delivery, performance risk, and growth potential. Set standards for metric definitions, data quality, and interpretation.
**Insights, Adoption & Advertiser Feedback**: Partner with Marketing Science, Sales, and Product to translate analysis into advertiser-facing insights and best practices. Design measurement plans and experiments quantifying how adoption affects delivery, ROAS, retention, and long-term value. Build systematic feedback loops converting advertiser input into quantified themes and prioritized product opportunities.
**Strategy, Forecasting & Business Impact**: Partner with Ads Sales leadership to segment demand, size opportunities, forecast outcomes, and inform strategies. Partner with Ads Product leadership to estimate advertiser value, prioritize roadmap, and measure business impact of product launches.
Required: 7+ years in data science or analytics within ads platforms, marketplaces, or performance-oriented B2B. Demonstrated business impact through advertiser demand growth, improved delivery/ROAS, stronger retention, or strategic decisions. Strong SQL and Python/R with depth in measurement, experimentation, causal inference, segmentation, benchmarking, and forecasting. Exceptional cross-functional communication with sales and product leaders; hands-on approach to ambiguous problems.
Strongly preferred: Experience at high-performing ads businesses with broad cross-functional data science roles. Hands-on familiarity with ad delivery, auctions, measurement, attribution, conversion signals, and advertiser lifecycle. Experience turning customer feedback into product priorities and evidence-backed best practices.
