Lead Data Scientist

8+ years experience in Data Science, preferably on recs/search/ranking with shipped impact. Strong Python and SQL; comfort with Spark. Fluency in ranking evaluation (NDCG@K, MAP, MRR, calibration, coverage/diversity) and awareness of exposure/selection bias. Fluency in experiment design and connecting offline metrics to online outcomes. Ability to translate product goals into loss functions, features, and specs engineers can build. Familiarity with LLMs/embeddings evaluation in offline and online.

Size and prioritize new recommendation surfaces, intents, and cohorts. Define and own the evaluation framework, including north star, guardrails, and Objective & Eval Contract per surface. Quantify correlation between offline and online metrics. Create leading indicators to predict long-term outcomes. Build the measurement architecture for trustworthy downstream metrics. Design and run advanced experiments with clear stop/go criteria. Codify schemas, freshness, leakage, and drift checks with Analytics and Data Engineers. Evaluate and prototype LLMs/embeddings for measurable improvements. Write decision memos, align cross-functional teams, and drive decisions with trade-offs and risks.