OpenAI is looking to build a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more, by developing a scalable forecasting platform to help understand and anticipate business dynamics in an increasingly complex, usage-based world.
Requirements
- Extensive experience building production-ready models for time series applications.
- Proven track record of building adjustable and explainable forecast models for multiple planning cycles.
- 10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.
- Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
- Experience building or scaling forecasting platforms in a high-growth company.
- A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments.
- Deep hands-on expertise in forecasting and predictive modeling.
Responsibilities
- Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.
- Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.
- Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.
- Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
- Research and evaluate emerging tools and techniques in the forecasting space.
- Translate technical outputs into business-aligned recommendations and decision frameworks.
- Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.
Other
- Team leadership experience with a track record of building high-performing, engaged teams.
- Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.
- An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
- A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.
- The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it takes to succeed.
