About In-House Health

In House Health is a seed-stage startup that aims to help the global healthcare crisis marked by severe staffing shortages and rising nurse burnout. In-House Health develops a cutting-edge platform that empowers nursing teams to self-manage with unprecedented flexibility. Our innovative solution leverages a predictive AI algorithm to optimize nurse shift assignments.

In-House Health is backed by one of the largest VCs in the world, and the CEO is Ari Brenner, who previously founded a digital health company with a >$1B valuation.

About the role

We're looking for a Senior Data Scientist to build the prediction engine behind our staffing platform. You'll report directly to our VP R&D and work on real hospital data that directly shapes how nurses are scheduled.

• Census prediction: forecast how many patients each hospital unit will have, shift by shift, from hours to weeks ahead, using admissions, discharges, transfers, seasonality and hospital-specific patterns.
• Patient acuity: model how sick patients are and how much nursing care they need, based on clinical data such as vitals, diagnoses, orders and nursing assessments.
• Nursing workload: combine census and acuity into workload predictions that drive how nurse shifts are planned and assigned.
• Clinical data: work hands-on with EHR records and ADT feeds from hospitals: messy, incomplete and full of signal.
• Own models end to end, from exploration and validation to production and monitoring.

About you

• You are highly motivated and excited to work at an early-stage company
• 5+ years as a data scientist, with models running in production
• Strong hands-on experience with time-series forecasting and classification models
• Strong Python and SQL
• An advantage is given to those with experience in healthcare or clinical data (EHR, ADT, HL7/FHIR)