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.