SAIVA AI

ABOUT SAIVA AI SAIVA AI applies machine learning to make optimal use of electronic health data for the most vulnerable healthcare population. Our mission is to improve patient outcomes by augmenting clinical decision-making with the power of AI. Based in Silicon Valley, our team is a group of passionate healthcare technology veterans, engineers, and data scientists, including from Stanford University, leveraging cutting edge technology to predict patient risk and provide tools that drive timely intervention. POSITION DESCRIPTION As a data scientist, you will own the correctness of the SQL that powers our client portal KPIs and run causal impact analyses that connect product use to patient outcomes. Expect varied, investigative work across structured + unstructured clinical data- with others handling back-end, front-end, and production query optimization. RESPONSIBILITIES In this position you will: Be the source of truth for metric definitions & SQL: numerators/denominators, cohort windows, timezone handling, late-arriving data, backfills, and window functions across multi-table joins. Analyze product utilization vs outcomes (e.g., report opens vs rehospitalization windows), choose appropriate causal designs, and explain results and assumptions clearly. Compare best vs worst model performance across buildings/cohorts; propose actionable fixes to lift recall/precision where it lags. Work hands-on in SQL + Python (R acceptable), using notebooks for analyses; BI tool familiarity is a plus (not a deliverable). Requirements ~2–4 years in industry as a data scientist/econometrician/biostatistician with solid SQL and causal chops. Evidence of owning multi-table SQL with windowing and time logic, and of shipping causal/observational studies that influenced decisions. Comfortable selecting methods that fit the data (e.g., experiments when possible; otherwise event studies/DiD, matching/weighting, survival). Undergrad degree required in Econometrics, Statistics, or a closely related quantitative field (CS minor or equivalent skills a plus). Nice to have: prior healthcare outcomes work or first-author publication experience.