Machine Learning Data Scientist, Forecasting

Join OpenAI as a Senior Machine Learning Data Scientist to lead forecasting initiatives, build robust models, and drive data-driven decision-making across the organization. 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.

• •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.
• •Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks.
• •Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making.

• •A hybrid work model of 3 days in the office per week.
• •Relocation assistance to new employees.

• •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.
• •Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
• •Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0→1.