Machine Learning Data Scientist - Consumer Forecasting

Job summary

Responsibilities

We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting…

• Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains.
• Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
• Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability.
• Contribute to self-service forecasting tools and internal platforms, enabling teams across OpenAI to access and act on real-time predictions.
• Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches.

What they're looking for

• Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
• 7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.
• Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability.
• Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
• Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.

Tech stack

• Python
• SQL
• scikit-learn
• PyTorch
• TensorFlow