Senior Data Scientist

Synapse Health is seeking a Senior Data Scientist to take ownership of end-to-end modeling work across vendor matching, order routing, and supply chain optimization in DME operations. This role partners closely with data engineering to move models from experimentation to production and supports expansion into Revenue Cycle Management and Finance initiatives.

Key Responsibilities

• Own models end to end across vendor matching, order routing, or supply chain optimization, expanding into new problem areas as priorities shift
• Build components of confidence thresholds and decision logic that move the team’s efforts toward agentic AI
• Quantify the impact of your work using measurable results rather than assumptions
• Ship models end to end, from experimentation through production, in close partnership with data engineering
• Select appropriate technical approaches for well-scoped problems, including predictive ML, causal ML, reinforcement learning, or operations research, with support from senior team members on complex judgment calls
• Write clear technical documentation for your own work
• Participate in quarterly planning and take on leverage-sequenced pieces of the roadmap
• Remain flexible as scope expands into Revenue Cycle Management, Finance, and other domains
• Operate effectively in a fast-moving, sometimes ambiguous environment

Required Qualifications

• Master’s degree required in a quantitative field (Computer Science, Statistics, Data Science, Operations Research, or related)
• 4–7 years of data science experience
• Prior experience at an early-stage healthcare startup, including hands-on work with claims data and other healthcare data
• Strong technical foundation in standard predictive ML (classification, regression, forecasting)
• Hands-on proficiency in Python and SQL, including the ability to write, debug, and optimize production-quality code beyond notebook prototypes
• Comfort with the full software development lifecycle and fluency with GitHub workflows, including version control, branching strategies, pull requests, and code review
• Track record shipping ML models into production in partnership with data engineering
• Ability to produce clear technical documentation
• Effective verbal and written communication, including presenting findings to technical and non-technical stakeholders
• Strong analytical and organizational skills, including managing multiple workstreams and priorities
• Comfort working in high-pressure settings where priorities shift and requirements may not be fully defined

Technologies

• Python
• SQL
• GitHub

Problems You Will Contribute To

• Vendor matching: build and iterate on models that determine which vendor fulfills each incoming order
• Order routing: develop predictive models that flag orders at risk of delay based on historical patterns
• Supply chain optimization: apply frameworks and methods to identify and quantify specific bottlenecks
• Agentic AI: implement and test components of decision logic aligned with architecture led by more senior team members

Additional Strengths That May Stand Out

• Reinforcement learning for sequencing decisions over time
• Operations research methods including queueing theory, network flow optimization, and discrete event simulation
• Causal inference methods such as difference-in-differences, regression discontinuity, or heterogeneous treatment effects
• Health economics or healthcare claims data experience
• Exposure to agentic AI tools or frameworks

Benefits

• Professional growth opportunities with compelling career paths
• Healthy work-life balance supported by flexible paid time off (PTO)
• Comprehensive benefits package, including medical, dental, vision, STD & LTD insurance for full-time team members
• 401(k) savings plan with employer matching contributions