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OpenAI is seeking a Head of Data Science for its Strategic Finance team to drive data-driven decision-making and improve financial outcomes through advanced analytics and forecasting.
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.
- Develop accurate forecasts for product usage and revenue, compute consumption and their underlying drivers, allowing for real-time tracking of key metrics performance and trajectory.
- Become an expert in OAI’s data and systems, through partnership with Data Engineering, Finance, and other Data Science teams.
- Design and deliver dashboards for key metrics that impact financial performance.
- Lead metrics reviews with Strategic Finance and finance leadership to interpret trends from aforementioned dashboards and surface actionable insights.
- Drive automation of standardized reporting, analysis, and processes across our various revenue segments and compute spend.
- Build and mentor a high-performing team.
- Support critical business decisions with ad hoc analysis as needed.
- A MS/PhD in a quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS).
- 12+ years of experience in a Data Science role at a dynamic and outcome-driven organization.
- Proficiency in critical analytical tools including SQL.
- Extensive experience building production-ready models for time series applications.
- Built adjustable and explainable forecast models for multiple planning cycles.
- Experience conducting open-ended research projects on new forecasting methodologies.
- Exemplary ability to distill complex financial information into actionable insights for leadership.
- Excellent communication skills and “storytelling” ability when presenting data insights.
- The ability to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful.
- Knowledge of Python.
- Prior management experience.
- Hybrid work model of 3 days in the office per week.
- Relocation assistance to new employees.