Senior Data Scientist — Build Production ML & Inference Models on Industrial Data

We're a seed-stage AI company building a computable model of the global chemicals and materials economy. We're looking for a senior, hands-on data scientist to build production classification and inference models over rich industrial datasets — full-time for 2–3 months, with possible extension or conversion to permanent. The work: Profile and explore complex real-world datasets (chemical plants, supply chains, material grades) Build baselines, then define evaluation sets and metrics before modelling Ship classifiers and matching/inference models with measured error rates and written error analyses Use LLMs where they genuinely belong — extraction, constrained labelling, code generation — with proper evals, never open-loop guessing You: Have shipped models to production where being wrong had consequences, and can explain exactly how you validated them Strong Python, pandas, scikit-learn; solid statistical instincts Experience building LLM pipelines with real evaluation harnesses is a strong plus An independent operator — you'll be setting the standard here, not following one No chemistry background needed; we supply the domain expertise