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Hinge Health is seeking a Senior Data Analyst to serve as the senior individual contributor and AI champion for the Commercial Analytics & Data Science team. This role is central to how Hinge Health's commercial organization—CS, Partnerships/HSO, and Commercial leadership—understands and acts on data.
You will independently own the team's most complex and highest-stakes initiatives, including the CS KPI and partner reporting suite, the commercial dbt data layer, and the team's AI and self-service analytics portfolio. You will serve as the primary analytical thought partner to CS, Commercial, and Partnerships/HSO leadership, owning the framing, scoping, and delivery of high-impact analyses across client retention strategy, surgery intent analytics, program expansion, commercial performance, and performance guarantee reporting.
A primary mandate is AI leadership and scaling self-service analytics. The team has working proof points—an AFTR workflow, a first-generation Data Discovery Agent, and active AnswerBot development—and your job is to take those from promising to compounding. You will own the team's AI strategy as the dedicated AI champion, scaling the CSM AnswerBot (v2 rebuild in Claude), the Data Discovery Agent (v1 in production, v2 must reach organizational scale), and AFTR v2.0 (proven internally as a toil-reducer, v2.0 aims to surface it directly to stakeholders). You will drive the team's contribution to the Analytics OS—the long-term platform into which these tools are intended to be incorporated—and own Commercial Analytics' roadmap within it.
You will own and evolve the commercial dbt data layer and mesh architecture, drive CDM enhancements including program-specific modeling (migraines, WPH, GI) and user-level pain reporting updates, and partner with analytics engineers and data engineers to ensure commercial data flows reliably from upstream services into reporting-ready tables.
You will communicate complexity simply and without condescension, explaining data models, statistical methodologies, and pipeline failures differently to CSMs, CS VPs, and data engineers. You will uplevel team analytical capability through documentation, structured knowledge transfer, ad hoc coaching, and mentoring through design reviews and real pairing.
The team operates lean and moves fast. This role requires someone who can independently lead multi-quarter analytical initiatives end-to-end with full autonomy, navigate complex cross-functional dynamics, manage stakeholder relationships without formal authority, and absorb organizational friction so the rest of the team can focus on the work. You are technically deep in SQL, dbt, and cloud data platforms and use that depth in service of framing strategy and owning methodology, not just executing it.
Hinge Health leverages software, including AI, to largely automate care for joint and muscle health, delivering improved member outcomes and cost reductions for clients. The platform addresses a broad spectrum of MSK care—from acute injury to chronic pain to post-surgical rehabilitation—and helps members engage in exercise therapy from anywhere.
The role is based in San Francisco HQ and follows a hybrid working model with 3 days per week in-office required. The office is dog-friendly.
REQUIREMENTS:
- Bachelor's degree in a quantitative field or equivalent professional experience
- 3+ years of experience as a data analyst with a demonstrated track record of owning complex, cross-functional analytical work in a commercial or product environment
- Sufficient technical depth in SQL, Python, and cloud data platforms (Databricks, Snowflake, BigQuery, or equivalent) to shape data architecture decisions, scope data model work, and partner credibly with analytics engineers
- Experience delivering strategic analytical work to VP+ stakeholders—including framing ambiguous problems, developing methodology under uncertainty, and presenting results to people who will challenge you
- Demonstrated ability to drive organizational alignment on data definitions, methodology, or reporting strategy across CS, Product, and engineering stakeholders without relying on formal authority
- Deep healthcare industry knowledge—clinical, payer, provider, or digital health; the team's work (concurrent care, clinical outcomes, commercial contracting, payer reporting) demands fluency that only comes from having worked in it
PREFERRED QUALIFICATIONS:
- Experience serving as a dedicated AI champion on an analytics team—not just a power user or early adopter, but someone who has taken existing AI proof points and scaled them into reliable, compounding capabilities that other people depend on
- Track record of communicating analytical complexity to non-technical stakeholders clearly and without jargon
- Prior experience building or leading self-service analytics platforms—including the governance, documentation, and training that makes self-service actually work
- History of mentoring analysts and raising team capability through shared standards, design review, and direct coaching
- Background in a lean, high-ownership team where you had to set your own analytical agenda rather than receive it
