Machine Learning Data Scientist - Consumer Forecasting

About the role

OpenAI's Strategic Finance Data Science team is building a Forecasting pillar, and is hiring a senior Machine Learning Data Scientist as one of its founding members. The role is based in San Francisco with a hybrid schedule of three days per week in the office, and relocation assistance is offered.

What you'll do

• Build statistical and machine learning forecasting models spanning product, finance, infrastructure, and go-to-market needs.
• Own the full modeling lifecycle: scoping, feature engineering, prototyping, experimentation, deployment, monitoring, and explainability.
• Productionize interpretable forecasts for user growth, revenue, LTV, compute consumption, and profitability.
• Contribute to self-service forecasting tools and internal platforms for teams across the company.
• Explore emerging approaches such as TimeGPT, LLM extensions, causal and hybrid forecasting, and turn results into executive-level recommendations.

Requirements

• MS or PhD in a quantitative field such as statistics, computer science, economics, or operations research.
• 7+ years in applied data science with hands-on forecasting, predictive modeling, or marketplace systems.
• Strong time-series expertise and judgment about performance, explainability, and scalability trade-offs.
• Proficiency with Python, SQL, scikit-learn, PyTorch/TensorFlow, and forecasting libraries, plus production model monitoring and maintenance.
• Excellent communication skills and comfort leading ambiguous 0→1 projects.