Product Manager – Data

🔥 23 minutes ago

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PurpleLab

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

🏥 Healthcare

💊 Pharmaceuticals

☁️ SaaS

💰 $12.7M Series A - Purple Labs on 2007-09

Healthcare • Pharmaceuticals • SaaS

PurpleLab is a real-world data and analytics company that provides validated, standardized healthcare datasets and a multimodal analytics platform (HealthNexus®) to help life sciences, payers, providers, agencies/media, and financial clients turn real-world data into actionable insights. Their offering centers on large-scale claims, provider, eligibility, remittance, EHR, and mortality datasets (billed as 16B+ annual claims) and supports real‑world evidence, campaign measurement, network intelligence, and operational analytics. PurpleLab positions itself as a flexible partner offering data access, pre-built analytics, and full-service consulting to accelerate drug development, advertising measurement, payer/provider network optimization, and other healthcare analytics use cases.

📋 Description

• 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

• 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)