Principal Product Manager, Data Products & Integrations

BranchLab•Boulder, CO

5d•$175,000 - $200,000•Hybrid

About The Position

BranchLab is transforming healthcare commercialization with Pathwai™, the industry’s first Semantic Activation Platform. Our AI-native technology helps leading healthcare organizations and their agencies make smarter commercialization decisions and connect patients, providers, and caregivers to life-improving therapies and resources. Built for the evolving privacy landscape, BranchLab improves commercialization performance without relying on individual-level health information. By modernizing the industry’s technical infrastructure, we help organizations operate more efficiently and responsibly while improving how healthcare audiences are understood, reached, and engaged. BranchLab is helping build a more intelligent, efficient, and responsible model for healthcare commercialization. We’re hiring a Principal Product Manager to lead our data products and integrations strategy. This role will define how BranchLab packages, governs, distributes, and scales identity, audience, activation, and partner-facing capabilities across our platform and ecosystem.

Requirements

8+ years of product management experience, ideally with data-heavy, platform, identity, audience, adtech, martech, healthcare data, or integration products.
Demonstrated ability to turn ambiguous data and infrastructure opportunities into clear product strategy, roadmap priorities, and customer-facing value propositions.
Strong understanding of data products, APIs, data pipelines, partner integrations, data quality, measurement, and platform scalability.
Experience working cross-functionally with engineering, data science, commercial, privacy, legal, and customer-facing teams.
Ability to evaluate tradeoffs across customer demand, revenue potential, strategic differentiation, feasibility, privacy risk, operational complexity, and reuse.
Strong communication skills, including the ability to represent product strategy in customer, partner, executive, and go-to-market conversations.
High-agency working style with comfort operating in fast-paced environments where priorities evolve and structure is still being built.
Commitment to building rigorous, privacy-safe products for regulated healthcare commercialization use cases.

Nice To Haves

Experience with identity resolution, graph products, tokenization, audience activation, clean rooms, or healthcare media measurement.
Familiarity with healthcare commercialization, pharmaceutical marketing, regulated data environments, or privacy-preserving data collaboration.
Experience building partner ecosystems, integration marketplaces, self-serve APIs, or reusable platform capabilities.
Comfort translating technical data concepts into commercial narratives, enablement materials, and executive-level recommendations.
Experience defining product success metrics across adoption, revenue influence, quality, match rate, latency, support burden, and customer outcomes.

Responsibilities

Own product strategy for high-impact data products, identity graph capabilities, and ecosystem integrations.
Define how BranchLab’s data assets should be packaged, distributed, and measured for customer and commercial impact.
Partner across Product, Engineering, Data Science, Privacy, Legal, Partnerships, Sales, Customer Success, and Operations to turn strategy into scalable platform capabilities.
Prioritize roadmap investments based on customer value, revenue opportunity, reuse, privacy risk, implementation complexity, and long-term differentiation.
Help shape the future of privacy-first healthcare commercialization by building data products that are rigorous, compliant, and designed for real-world use.
Serve as the product leader for data products and integrations, bringing product discipline to how BranchLab develops reusable data assets, scales integrations, and delivers measurable value to customers and partners.
Lead data product and identity strategy: Define the strategic direction for BranchLab’s identity graph capabilities, audience products, activation workflows, and reusable data assets. Clarify how these capabilities are positioned, differentiated, governed, measured, and incorporated into customer-facing products.
Shape distribution and integration strategy: Determine how data products should reach customers, partners, platforms, APIs, clean rooms, marketplaces, internal systems, and direct customer workflows. Create a product-led integrations roadmap that prioritizes high-value ecosystem connections and reusable integration patterns.
Turn complex data capabilities into scalable products: Manage identity and data products as reusable platform assets with clear customer segments, value propositions, documentation, access models, adoption targets, quality standards, and lifecycle plans. Help determine what should be created, scaled, maintained, consolidated, or retired.
Lead cross-functionally from strategy through adoption: Partner closely with Engineering, Data Science, Privacy, Legal, Partnerships, Sales, Customer Success, and Operations to translate strategy into delivery plans, commercial enablement, partner decisions, and measurable adoption outcomes.
Focus Areas: Identity graph strategy and product positioning, Partner and platform integration strategy, Tokenization, identity resolution, and interoperability models, Direct integrations with healthcare, media, and activation partners, Reusable integration patterns, APIs, standards, and observability, Distribution strategy across platforms, clean rooms, marketplaces, and direct workflows, Data product packaging, lifecycle management, and commercial enablement, Privacy-safe product design for regulated healthcare commercialization use cases.
Establish an approved strategy and roadmap for data products, identity graph capabilities, and integrations.
Increase adoption of prioritized data products across customers, partners, and internal teams.
Create clearer packaging, positioning, and distribution models that support new and expanded commercial opportunities.
Reduce duplicative or one-off integration work through reusable standards, patterns, and prioritization frameworks.
Improve visibility into data product performance through usage, quality, latency, match rate, support, and customer outcome metrics.
Build a clear governance model for data product lifecycle decisions, including launch, scale, maintenance, consolidation, and retirement.