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Data Scientist, Ads Demand

OpenAI

Data Scientist, Ads Demand is a still-open role at OpenAI on Jobrow. Location: On-site · San Francisco · California · United States. Listed pay: $293k–$515k. Sourced from the company's public Ashby board. First seen 2 months ago; last confirmed 9 days ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
$293k–$515k
Workplace
On-site
Location
San Francisco · California · United States
First seen
2 months ago
Last seen
9 days ago
Board
Ashby
Apply

About this role

About the Role OpenAI's ads business is scaling quickly.

  • Seniority: mid

Location & pay

On-site · San Francisco · California · United States Listed pay on Jobrow: $293k–$515k.

Source

Jobrow reads the public Ashby board for OpenAI. First seen 2 months ago; last seen 9 days ago. We are not the employer — apply only on the company ATS.

Posting

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-facing insights, benchmarks, and best practices. - Design measurement plans and experiments that quantify how best-practice and product adoption affect delivery, ROAS, retention, and long-term advertiser value. - Build a systematic feedback loop that converts advertiser input into quantified themes and prioritized product opportunities, then measures whether shipped changes improve outcomes. Strategy, Forecasting & Business Impact - Partner with Ads Sales

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