Senior Data Scientist

About the role

Who We Are :

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.

Since 2016, with decades of industry and leadership experience, we've delivered tech-based solutions that help our partners to modernize operations, improve coordination, and reduce administrative burdens. By taking on operational and financial complexity, we're redefining how DME works for providers, prescribers, and patients. We are proud to offer work that matters, on a mission that matter s .

Learn more at SynapseHealth.com and on Synapse Health’s LinkedIn .

What We Need :

The Sr. Data Scientist reports directly to the Director of Data Science and Analytics (or a Staff Data Scientist, depending on team structure). Our operations team processes tens of thousands of DME orders every day, and we've now processed millions of orders overall — giving us the data to build real prediction engines rather than just react order by order. This role works generally independently and collaboratively, contributing to the moderately complex pieces of the roadmap: you own well-scoped problems end to end, but you're not expected to define the technical strategy for an entire domain the way a Staff Data Scientist would.

The problems you'll contribute to include:

Vendor matching — build and iterate on models that decide which vendor fulfills each incoming order

Order routing — build predictive models that flag orders at risk of delay based on historical patterns

Supply chain optimization — apply the frameworks and methods a Staff Data Scientist or the Director has set up to find and quantify specific bottlenecks

Agentic AI — implement and test components of the decision logic that more senior team members are architecting

This mandate isn't fixed — as Synapse's data science footprint grows into Revenue Cycle Management, Finance initiatives like anomaly detection, and beyond, this role is expected to flex alongside the rest of the team.

What You Will Do :

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 the confidence thresholds and decision logic that push the team's work toward agentic AI

Quantify the impact of your own work 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 well-scoped problems — predictive ML, causal ML, reinforcement learning, or operations research — with support from senior team members on trickier judgment calls

Write clear technical documentation for your own work

Participate in quarterly planning, taking on clearly leverage -sequenced pieces of the roadmap

Stay flexible as the team's scope expands into Revenue Cycle Management, Finance, and other domains

Comfortable operating in a fast-moving, sometimes ambiguous environment

Note: These responsibilities reflect the general nature and scope of the role but are not exhaustive. Responsibilities may evolve to meet changing business needs.

What You Have :

At Synapse Health, we’ve intentionally built a culture rooted in kindness, collaboration, and creativity, qualities we consider essential for every team member. Additional requirements include:

Education — Master's degree required in a quantitative field (Computer Science, Statistics, Data Science, Operations Research, or related)

Experience — 4–7 years in data science

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, f orecasting)

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 models into production, in partnership with data engineering

Able to write clear technical documentation for your own work

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

What Sets You Apart :

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:

Reinforcement learning for sequencing decisions over time

Operations research methods (queueing theory, network flow optimization, discrete event simulation)

Causal inference — difference-in-differences, regression discontinuity, or heterogeneous treatment effects

Health economics or healthcare claims data experience

Exposure to agentic AI tools or frameworks

What Sets Us Apart :

Work is a part of life , but at Synapse Health, we believe it should be meaningful and enjoyable. We’re committed to helping our team members thrive personally and professionally, which is why our benefits include:

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

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senior From the job title

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full time

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Remote, US

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