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Product Manager - Data

PurpleLab Inc

📍 Wayne, Pennsylvania, US0💼 Full-time💰 80,000 – 100,000 USD/year🕐 5/23/2026
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Role overview

PurpleLab Inc is hiring for the Product Manager - Data role in Wayne, Pennsylvania, US. It is full-time, Mid-level level, in the Tech sector. The stated pay for this position is 80,000 – 100,000 USD/year. It was posted 5/23/2026.

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Role
Product Manager - Data
Company
PurpleLab Inc
Location
Wayne, Pennsylvania, US
Work mode
On-site
Employment
Full-time
Seniority
Mid-level
Sector
Tech
Salary
80,000 – 100,000 USD/year
Posted
5/23/2026

Description

Description: We’re looking for a Product Manager to own our reference data portfolio. In this role, you’ll be responsible for the datasets, attributes, and definitions that customers rely on to interpret healthcare claims — including payer data (plan identifiers, plan type, line of business, parent organization, channel, network, funding type, PBM relationships), SDOH (social determinants of health), mortality, formulary offerings, and the broader set of reference datasets customers use to filter, segment, and analyze claims. 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 Requirements: Required: • 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 Nice to have: • 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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