Senior Data Scientist

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  &  LT