Senior Data Analyst

About this role

ABOUT THE ROLE

The Commercial Analytics & DS team is the analytical engine of Hinge Health's commercial business – the team that CS, Partnerships/HSO, and Commercial leadership rely on for the data, metrics, and strategic thinking that drive client retention, program growth, and commercial decision-making. We build the self-service analytics infrastructure, AI-powered workflows, and high-stakes deliverables that define how HH's commercial organization understands and acts on its data.

We are looking for a Senior Data Analyst to serve as the team's senior individual contributor, dedicated AI champion, and organizational thought partner. You will independently own the team's most complex and highest-stakes initiatives – from the CS KPI and partner reporting suite to the commercial dbt data layer to the team's AI and self-service portfolio – and serve as the go-to analytical authority for CS, Commercial, and Partnerships/HSO leadership. AI ownership is a primary mandate, not a side contribution: the foundations are real (a working AFTR workflow, a first-generation Data Discovery Agent, active AnswerBot development), and your job is to take those proof points from promising to compounding. You are technically deep in SQL, dbt, and cloud data platforms – and you use that depth in service of framing strategy and owning methodology, not just executing it. The team operates lean and moves fast. If the role you are imagining requires someone to write tickets and execute – this is not it.

WHAT YOU'LL ACCOMPLISH

STRATEGIC ANALYTICS & COMMERCIAL LEADERSHIP

- 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, client health, and performance guarantee reporting

- Own and maintain the CS KPI and Bowler reporting suite – the dashboards and metrics CS leadership depends on to track commercial performance

- Lead multi-quarter analytical initiatives end-to-end with full autonomy; the team's P0 initiatives (Analytics OS, client hub, retention model) should not require the hiring manager to carry them

- Navigate complex cross-functional dynamics: manage stakeholder relationships without authority, push back constructively when data is being misread, drive alignment on methodology even when it is inconvenient, and absorb organizational friction so the rest of the team can focus on the work

AI LEADERSHIP & SELF-SERVICE ANALYTICS

- Own the team's AI and self-service strategy as the dedicated AI champion for Commercial Analytics – the counterpart to the AI lead role on HH's product-side Data Science team, with equivalent mandate and accountability

- Scale and compound the team's existing AI portfolio: the CSM AnswerBot (v2 rebuild in Claude, a recurring stakeholder ask with active external pressure on timelines); the Data Discovery Agent (DDA) (v1 is in production and demonstrates the concept works; v2 must reach the reliability and scale the organization needs); and AFTR (Add Field To Report) v2.0 (proven internally as a meaningful toil-reducer; v2.0's ambition is to surface it directly to stakeholders so they can extend their own reports without analyst involvement)

- Drive the team's contribution to the Analytics OS – the long-term platform into which the AnswerBot, DDA, and AFTR are intended to be incorporated; own Commercial Analytics' roadmap within it and ensure the tools you are scaling are being built toward that destination from day one

- Use AI-assisted tools (Claude Code, Cursor, and equivalents) actively and with genuine curiosity; bring a real appetite for agentic workflows, and contribute to Matik-powered reporting automation that reduces the team's dependency on manual, recurring analytical requests

DATA MODELING & COMMERCIAL INFRASTRUCTURE

- Own and evolve the commercial dbt data layer and mesh architecture – keeping it clean, well-tested, and scalable

- Drive CDM enhancements including program-specific modeling (migraines, WPH, GI) and user-level pain reporting updates tied to the NRS/VAS transition

- Partner with analytics engineers and data engineers to ensure commercial data flows reliably from upstream services into reporting-ready tables; advocate for upstream instrumentation best practices with Engineering partners

COMMUNICATION, TEACHING & TEAM ELEVATION

- Communicate complexity simply and without condescension – you can explain a data model architecture, a statistical methodology, or a pipeline failure to a CSM, a CS VP, and a data engineer, and the explanation lands differently each time because you know your audience

- Uplevel team analytical capability through documentation, structured knowledge transfer, ad hoc coaching, and building shared practices

- Mentor through design reviews, analytical critique, and real pairing – actively raising the bar for what good looks like

BASIC QUALIFICATIONS

- 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,…