Arcadia is dedicated to happier, healthier days for all. We transform diverse data into a unified fabric for health. Our platform delivers actionable insights for our customers to advance care and research, drive strategic growth, and achieve financial success. For more information, visit arcadia.io. Why This Role Is Important To Arcadia The Technical Product Manager, Life Sciences sits at the intersection of product strategy and engineering execution, embedded directly with our teams to turn complex healthcare data and platform capabilities into products our customers rely on. This role owns the technical depth of the product lifecycle while keeping the team anchored to customer value and business outcomes. You will be the connective tissue between Product and Engineering: fluent enough in the technical stack to make real-time tradeoff decisions with engineers, and disciplined enough in product craft to keep the roadmap grounded in customer impact. This is a hands-on, technical product role for someone energized by the details of how things work, not just what gets shipped. What Success Looks Like In 3 Months Develop working fluency in Arcadia's platform architecture, data model, and the technical stack of your assigned engineering team. Build trusted, credible working relationships with your engineering counterparts, joining sprint ceremonies and grooming sessions. Take ownership of a product area's backlog and begin active prioritization grounded in customer and technical impact. Demonstrate the ability to hold your own in a technical conversation about pipeline architecture, data, or implementation tradeoffs. In 6 Months Ship one or more meaningful product increments in close partnership with engineering, on a predictable delivery cadence. Establish clear product and delivery metrics, and use them to guide prioritization and stakeholder reporting. Be a go-to resource for engineering on requirements clarity, scope tradeoffs, and customer context. Lead structured technical discovery (data investigation, feasibility checks, pipeline architecture discussions) that informs roadmap decisions. In 12 Months Be recognized as the product owner and technical subject-matter expert for your portfolio, trusted by engineering and business stakeholders alike. Drive roadmap strategy that balances near-term delivery with long-term platform scalability and technical health. Proactively identify and act on opportunities to reduce technical debt, improve data quality, or unlock new technical capability. Mentor peers on how to work effectively with engineering teams and contribute to broader product-engineering process improvements. Responsibilities Own product strategy and roadmap for a defined portfolio within Arcadia's platform, partnering day-to-day with an embedded engineering teams through the full SDLC. Translate business goals, customer needs, and technical realities into clear requirements, acceptance criteria, and well-scoped increments engineering can execute against. Engage deeply with engineering on data pipeline, data models, and enrichment asking the right technical questions and making informed calls when priorities conflict. Run and participate in agile ceremonies: backlog grooming, sprint planning, sprint reviews, and incident/RCA reviews, ensuring engineering has what it needs to move fast without losing quality. Deconstruct ambiguous or large-scale goals into MVPs and iterative delivery plans, adjusting scope based on technical constraints and customer feedback. Use SQL and product/data instrumentation to self-serve answers, validate hypotheses, and make data-informed prioritization decisions. Replicate, triage, and help troubleshoot complex product issues alongside engineering, escalating and documenting bugs and workarounds as needed. Communicate roadmap progress, technical risks, and tradeoffs clearly to both technical and non-technical stakeholders. Partner with agentic designers, operations, commercial, marketing, and analytic teams to ensure what engineering ships is adopted and drives measurable value. Advocate for a healthy balance between shipping new capability and managing technical debt, performance, and platform scalability. Requirements Bachelor's Degree in Computer Science, Data Science, Statistics, or a related field (or equivalent professional experience) Requirements 4–7+ years of product management experience, with meaningful time spent working shoulder-to-shoulder with engineering teams in Agile/Scrum environments. Proven track record taking products from requirements through SDLC to launch, including scoping MVPs and iterating post-launch. Experience engaging in real technical tradeoff discussions architecture, APIs, data flows, scalability, and implementation approach. Healthcare, health-tech, or complex B2B data/SaaS experience strongly preferred; population health, value-based care, or interoperability experience is a plus. Technical Fluency Hands-on SQL proficiency, comfortable writing queries to self-serve analysis and validate product decisions. Working understanding of database and data-platform technologies (e.g., Snowflake, cloud data warehouses) and how data model design affects product capability. Comfort partnering with engineers on API design, system architecture, and technical constraints without needing everything translated into non-technical terms. Qualities & Skills Strong ownership mentality with a bias toward action and hands-on execution. Excellent written and verbal communication; able to move fluidly between engineering detail and executive-level summary. Comfortable operating in ambiguity, breaking large problems into deliverable increments. Calm, confident facilitator of trade-off conversations across product, engineering, and business stakeholders. Attention to detail and a commitment to clear, current documentation. Would Love For You To Have Experience with healthcare data standards or interoperability frameworks (e.g., FHIR) and regulatory-grade data environments. Exposure to AI/ML or GenAI-enabled product capabilities, including retrieval-augmented generation, automation, or predictive analytics. Experience with BI/visualization tools (Tableau, Power BI, Looker, or similar) and large-scale data platforms (Snowflake, Redshift, Databricks, or similar). A background in a hard science (math, statistics, computer science, or engineering) or prior experience as a software engineer or data analyst. Benefits The chance to work shoulder-to-shoulder with a team of extremely talented, dedicated engineers and product builders. Deep, focused exposure to Arcadia's platform architecture, data model, and engineering practices. Be part of a mission-driven company transforming healthcare by changing the way patients receive care. A flexible, remote-friendly company with personality and heart. Employee-driven programs and initiatives for personal and professional development. Membership in the Arcadian and Barkadian community.
