Level

OpenAI

Data Scientist, Ads Demand

OpenAI is hiring a Data Scientist, Ads Demand in San Francisco, United States. It pays $293k-$515k a year and Level rates it ; you can apply on OpenAI.

Level's read on this job

  • Little AI ●○○○ is how Level rates this data scientist role: aI is not part of the work.
  • Pay on this posting starts 76% higher than the typical data scientist posting on Level.
  • The posting mentions AI research, data science and sql among its tools and skills.
  • Level classes it as a senior role.
  • OpenAI has 795 other open roles on Level.

AI in this role

Build measurement frameworks and insights for ad demand health and marketplace value at OpenAI.

ai-researchdata-sciencesqlexperimentationcohort-analysisforecasting



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 leadership to segment demand, size opportunities, forecast outcomes, and inform demand strategies, sales plays, and investments.

  • Partner with Ads Product leadership to estimate advertiser value, prioritize the roadmap, and measure the business impact of product launches.


What We're Looking For

Required

  • 7+ years of experience in data science or analytics within an ads platform, marketplace, or performance-oriented B2B business.

  • Demonstrated business impact through advertiser demand growth, improved delivery or ROAS, stronger retention, or decisions that changed product and sales strategy.

  • Strong SQL and Python or R, with depth in measurement, experimentation, causal inference, segmentation, benchmarking, and forecasting.

  • Exceptional cross-functional communication and influence with both sales and product leaders, plus a hands-on approach to ambiguous, 0-to-1 problems.

Strongly Preferred

  • Experience at a high-performing ads business where data scientists work broadly across Sales, Marketing Science, and Product rather than in a narrow silo.

  • Hands-on familiarity with ad delivery, auctions, measurement, attribution, conversion signals, and the advertiser lifecycle.

  • Experience turning customer feedback into product priorities and evidence-backed best practices that improve advertiser outcomes.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

How we rate this

Data Scientist, Ads Demand at OpenAI rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchData ScienceSQLExperimentationCohort AnalysisForecasting

Also common in data scientist jobs at this level

Pay

This job starts at
$293k
Typical data scientist job
$166k

This posting starts 76% above the typical data scientist job. See data scientist jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Tell me about a project where data science was part of your work. What did you do?
  3. Tell me about a project where sql was part of your work. What did you do?
  4. Tell me about a project where experimentation was part of your work. What did you do?
  5. Tell me about a project where cohort analysis was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Research, Data Science, SQL, Experimentation, and Cohort Analysis. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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