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Synapse Health

Staff Data Scientist

RemoteNot specified. Estimate: United States · 74% confidence
Published
Role
Data Science
Experience
Staff
Employment
Full-time
Salary not disclosed
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The listing doesn't say where it hires from. It may hire in United States (74% confidence). This is an estimate, not an eligibility rule; verify before applying.Signals: employment terms.

No BS summary

Staff-level data scientist for healthcare/DME operations, 7+ years, senior independent IC. Must have a master's in a quantitative field, early-stage healthcare startup experience with claims/healthcare data, and strong Python, SQL, predictive ML, GitHub, and end-to-end ML production experience.

Core skills

Predictive MLOperations ResearchAgentic AI

Required skills

PythonSQLGitHubClassificationRegressionForecasting

Optional skills

Reinforcement LearningQueueing TheoryLittle's LawNetwork Flow OptimizationDiscrete Event SimulationCausal InferenceDifference-in-DifferencesRegression Discontinuity

What you'll do

  • Build and own models across vendor matching, order routing, and supply chain optimization, expanding into new problem areas as priorities shift
  • Architect confidence thresholds and decision logic that let systems act autonomously once proven trustworthy, pushing the team's work toward agentic AI
  • Quantify the counterfactual for your work: prove out impact with real numbers, not assumptions
  • Ship models end to end, from experimentation through production, in close partnership with data engineering
  • Apply the right technical approach to the problem — predictive ML, causal ML, reinforcement learning, operations research, or causal inference — rather than defaulting to one toolkit
  • Mentor senior data scientists on the team, raising the technical bar without formal management responsibility
  • Write clear technical design docs and hold your own work to a high bar
  • Partner with the Director and the rest of the team to break work into quarterly, leverage-sequenced priorities
  • Stay flexible as the team's scope expands into Revenue Cycle Management, Finance, and other domains

What they require

  • Master's degree required in a quantitative field (Computer Science, Statistics, Data Science, Operations Research, or related)
  • 7+ years in data science, with a track record as a highly independent, senior IC
  • Prior experience at an early-stage healthcare startup, with hands-on expertise in claims data and other healthcare data.
  • Strong technical foundation in standard predictive ML (classification, regression, forecasting)
  • Strong hands-on proficiency in Python and SQL — able to write, debug, and optimize production-quality code, not just prototype in a notebook
  • Understands the full software development lifecycle and works fluently with GitHub — version control, branching strategies, pull requests, and code review — as a standard part of shipping models into production.
  • Track record shipping ML products end to end, from experimentation through production, in close partnership with data engineering
  • Able to write technical design docs and hold your own work to a high standard
  • Demonstrate effective verbal and written communication skills, including presenting findings to technical and non-technical stakeholders
  • Demonstrate strong analytical and organizational skills, managing multiple workstreams and priorities
  • Comfortable operating in a high-pressure, ambiguous environment where priorities shift and requirements aren't always fully defined
  • Preferred: Candidates are expected to have hands-on experience in several — not necessarily all — of these areas, along with the ability to quickly learn new ones
  • Preferred: Offline and online reinforcement learning for sequencing decisions that improve in-flow/out-flow over time
  • Preferred: Operations research methods (queueing theory / Little's Law, network flow optimization, discrete event simulation) applied to supply chain or logistics
  • Preferred: Rigorous causal inference skills — estimating heterogeneous treatment effects and applying quasi-experimental designs like difference-in-differences and regression discontinuity
  • Preferred: Deep expertise in health economics — able to rigorously evaluate ROI and connect data science impact directly to business value
  • Preferred: Experience building agentic AI tools, with a point of view on how emerging AI capabilities could unlock future use cases beyond what's scoped today

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

At Synapse Health, we're streamlining the durable medical equipment (DME) process. We manage intake, documentation, routing, claims, billing, and patient support. Our model reshapes how DME is delivered and experienced.

HealthcareMid-size

Details

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Salary not disclosed