Responsibilities

• Define the long‑term forecasting roadmap and establish architectural standards for the entire company.
• Lead the architectural design of complex ML systems, ensuring they are scalable, maintainable, and integrated seamlessly with the broader engineering stack.
• Architect reusable, platform‑level forecasting frameworks to be used by other Data Science teams.
• Own the development of tier‑1 models—those with the highest business risk or technical complexity—using advanced statistical, deep learning, or reinforcement learning techniques.
• Tackle high‑ambiguity challenges, such as integrating causal inference or deep learning into global forecasts.
• Act as the subject‑matter expert for Generative AI; design RAG architectures, evaluate foundation models, and establish fine‑tuning protocols for proprietary data.
• Define the team’s technical standards for CI/CD, model versioning, and automated testing.