Staff Data Scientist

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*.*

The Staff Data Scientist reports directly to the Director of Data Science and Analytics. 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 is a senior, highly independent IC: you don't manage people, but you're expected to own hard problems end to end, mentor senior data scientists on the team, and bring the technical judgment of someone who could.

The problems we need to solve include:

• Vendor matching — deciding which vendor fulfills each incoming order, optimizing for patient experience, delivery speed, and cost. Requires strong predictive ML (classification, regression) and optimization skills.
• Order routing — identifying the most efficient path from order creation to delivery and flagging orders at risk of delay. Requires predictive ML and, ideally, reinforcement learning for sequencing decisions over time.
• Supply chain optimization — finding root\-cause bottlenecks across in\-flow and out\-flow and quantifying the counterfactual impact of fixing them. Requires operations research methods (queueing theory, network flow optimization, discrete event simulation) and causal inference.
• Agentic AI — evolving these systems from ones that recommend actions to ones that take them directly, once proven trustworthy. Requires experience building agentic AI tools and designing confidence thresholds and decision logic for autonomous action.

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 and take on new problem areas alongside the rest of the team.

• 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

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

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 — 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

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:

• Offline and online reinforcement learning for sequencing decisions that improve in\-flow/out\-flow over time
• Operations research methods (queueing theory / Little's Law, network flow optimization, discrete event simulation) applied to supply chain or logistics
• Rigorous causal inference skills — estimating heterogeneous treatment effects and applying quasi\-experimental designs like difference\-in\-differences and regression discontinuity
• Deep expertise in health economics — able to rigorously evaluate ROI and connect data science impact directly to business value
• 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

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

Privacy Policy