Sprinter Health is looking to solve the problem of limited access to healthcare, particularly preventive and chronic care, by bringing it directly to patients' homes. They aim to reduce avoidable ER costs and improve patient outcomes by leveraging data to optimize logistics, understand patient behavior, and manage clinical operations.
Requirements
- Worked with large, messy datasets to answer ambiguous, high-stakes questions
- Built dashboards or visualizations using Looker, Tableau, Grafana, Superset, or similar
- Written high-quality SQL across warehouses like BigQuery, Snowflake, or Redshift
- Experience with Python, Pandas, Scikit-learn, or ELK (Elasticsearch + Kibana)
- Exposure to GCP data tools like BigQuery, DataFlow, or DataForm
- Familiarity with healthcare data (claims, HL7, CCDAs, HIEs)
- Designed or analyzed growth experiments or user behavior funnels
Responsibilities
- Explore clinical, operational, and patient engagement data to surface actionable insights
- Analyze routing, capacity planning, and supply-demand dynamics across regions
- Identify drivers of preventive care engagement and patient follow-through
- Predict cancellations, risk, and future care needs using behavioral and clinical signals
- Design and evaluate A/B experiments across product, growth, and operations
- Support internal teams with dashboards, analytics, and ad hoc decisions
- Help shape the Data function’s standards, tooling, and processes as an early leader
Other
- 5+ years in data science, advanced analytics, or applied data modeling
- Influenced product, ops, or strategy decisions through data insight and storytelling
- Presented findings to leadership and collaborated with cross-functional teams
- Experience with logistics, routing, or operational optimization problems
- Communicated insights to C-level stakeholders or mentored junior talent
