**About the Role **This role focuses on building the strategic unit economics understanding of OpenAI, guiding sustainable growth to make it the most impactful company of our generation and beyond.
You will lead the development of foundational causal inference and data science models and frameworks to predict and quantify the drivers of customer lifetime value (LTV), translating deep data insights into strategic decisions and growth levers. The role requires both technical depth and executive-level communication.
This position is based in our San Francisco HQ with a hybrid work model (three days in office per week). Relocation assistance is available.
The Vision
- Build causal inference and predictive analytics capabilities to measure and forecast LTV across customer segments (B2C and B2B), and quantify the incremental impact of different actions or product features on customer LTV.
- Design customer “happy paths” by identifying adoption journeys that maximize lifetime value while ensuring customers gain the most from our ecosystem.
- Analyze price elasticity to guide product packaging, monetization, and pricing strategies.
In this role, you will:
- Partner with cross-functional teams (Finance, Product, Data Engineering, GTM, and other DS teams) to build causal inference and predictive models that drive business decisions.
- Develop and maintain LTV models across product lines and customer cohorts.
- Architect scalable frameworks and models that democratize economic insights for leadership and functional teams.
- Support strategic pricing and investment decisions with robust analytical and causal evidence.
- Lead cross-functional data science initiatives, ensuring analytical rigor, clarity, and timely delivery.
You might thrive in this role if you:
- Executive communication — ability to distill complex analysis into clear, actionable recommendations for leadership.
- Technical breadth — comfort spanning ROI analysis, causal inference, statistical modeling, and ML predictive models; strong experience with Python and SQL.
- Strategic judgment — ability to connect analytical insights to business impact, delivering the “so what” that informs leadership decisions.
- Collaboration and ownership — thrive in a fast-paced, cross-functional environment and proactively take projects from concept to delivery.
Qualifications
- MS or PhD in a quantitative field (Statistics, Economics, Applied Math, Operations Research, Computer Science, etc.).
- 7+ years of experience in applied data science, causal inference, or quantitative strategy.
- Proven record of delivering high-impact insights to executive leadership.
- Experience building scalable analytical frameworks and models that inform business decision-making.
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.
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