Product Manager - Data
Indexed description
If you like data that needs to be right — where a mis-mapped plan, a stale flag, or a missing NDC immediately shows up in a customer report — this role is for you. You’ll partner with data, methodology, and the broader product team to make sure our reference datasets are accurate, well-defined, well-documented, and evolving with the market. It’s a high-leverage seat for a PM who wants to build deep domain expertise across multiple healthcare data domains.
What You'll Do
- Own the roadmap and backlog for our reference data portfolio — payer, SDOH, mortality, formulary, and other reference datasets: which fields we carry, how they’re defined, how they’re sourced, and how they’re maintained over time
- Write clear PRDs, user stories, and data specs that translate customer needs into requirements engineering and data teams can build from
- Partner with develop to curate reference data across payer, SDOH, mortality, and formulary domains
- Monitor attribute quality — coverage, fill rates, mapping accuracy, drift over time — and prioritize fixes based on customer impact
- Track market and data-source changes that affect our reference datasets: payer M&A, plan rebrands, Medicare Advantage contract changes, PBM shifts, formulary updates, new SDOH data sources, and mortality data refresh cycles — and translate them into backlog updates
- Partner with commercial, customer success, and analytics teams to understand how customers actually use our reference datasets and where definitions need to sharpen
- Write and maintain data dictionaries, attribute definitions, and release notes so internal teams and customers can confidently use what we ship
- 2–5 years of experience in a product, analyst, data, consulting, or operations role — including direct exposure to product management practices (PRDs, sprints, backlogs)
- Working knowledge of healthcare data — medical claims, pharmacy claims, eligibility/enrollment files, or similar. You should be comfortable reading a data dictionary and talking about fields, values, and how they're used.
- Detail-oriented and quality-obsessed; you notice when a value looks off, and you care about getting definitions precisely right
- Strong analytical mindset; comfortable in spreadsheets, can profile a dataset to spot gaps or anomalies, and ideally have some SQL skills
- Excellent written communication; you can write a clear attribute definition that removes ambiguity rather than adding it
- Organized and proactive — you keep track of details, follow through on commitments, and don't need to be chased
- Comfortable working with technical teams and translating between business and engineering; experience working with offshore teams is a plus
- Curious about healthcare data broadly — how health plans are organized, how SDOH indices are constructed, how mortality data is sourced, how formularies are structured, and how all of this shows up in claims data
- Direct experience working with healthcare reference data (payer attributes, SDOH indices, mortality files, formulary/NDC mappings, or plan and network hierarchies)
- Familiarity with payer-side concepts: commercial vs. Medicare Advantage vs. Medicaid vs. Exchange, fully-insured vs. ASO, PBM carve-outs, risk adjustment, formulary management
- Experience with HIPAA-compliant data environments
- SQL proficiency; bonus for any exposure to Python, dbt, or BI tools (Looker, Tableau, Power BI)
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