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Clarify Health is an outcomes-focused analytics company partnering with 60+ health systems to align mission and margin across healthcare delivery. The company processes 900 million annual referrals and $1 trillion in downstream spending, providing the most complete picture of care economics through 300 million patient journeys and episode-level quality data across major payer contracts.
As Senior Product Analyst, you will own the analytics methodology and data infrastructure behind Clarify's customer-facing metrics. This is a hands-on role where you will:
**Own the data methodology:** Define and carry derived data points from development through QA into production, including episode triggers, provider attribution, cost standardization, and quality measure logic. Manage Clarify's reference data library spanning physician/facility mappings, medical code sets (ICD, HCPCS, NDC, DRG) and their service-line categorizations, and geographical data.
**Validate the numbers:** Prove metrics before release using reconciliation SQL, version-over-version comparisons, and impact analysis. Build standing data quality tests and completeness thresholds that must pass before data reaches customers. Run data refresh and delivery cadence for customer environments, working test failures to root cause with engineering.
**Turn requests into delivered analytics:** Scope feature requests from product, clinical, and customer teams. Write specifications and acceptance criteria, decide what you build versus what goes to engineers, and follow through to release. Settle cross-team methodology on attribution logic, referral definitions, and provider reference data. Validate AI-assisted tooling output against source data and set review standards.
You will work with SQL daily as your primary tool, with opportunity to develop scripting and pipeline skills. Every metric in Clarify's products traces back to logic you or your team defined, populated, and validated. This role is ideal for someone who knows healthcare data deeply, understands claims codes, and treats data accuracy as a personal responsibility.
**Requirements:**
- Bachelor's degree in quantitative, technical, or health-related field, or equivalent practical experience
- 5+ years in data analysis, healthcare analytics, or comparable data-heavy role
- Advanced SQL: query large datasets independently, build metrics from raw source records, define grain, defend every value
- Experience in AWS ecosystem and with industry-leading AI models, especially for code development
- Working knowledge of healthcare data (claims, provider, network data) and what codes on a claim represent
- Production data experience where tables refresh on schedule, other teams depend on output, and changes move through QA before release
- Clear writing: specifications, acceptance criteria, and decision records that engineers can act on and auditors can follow
**Preferred Qualifications:**
- Depth in healthcare domain (episode grouping, risk adjustment, quality measurement, provider/network reference data, CMS/NCQA measure specs, clinical value sets, HL7/FHIR/X12 standards)
- BI and dashboarding tools with track record of explaining analysis to non-technical audiences
- Recurring data quality checks you've set up yourself
- Python/PySpark experience
