Arbital Health operates an AI-powered adjudication platform and actuarial team that centralizes fragmented data, automates outcomes-based contract reconciliation, and delivers risk dashboards, insights for payers, providers, digital health.
Arbital Health is a rapidly growing healthcare technology and actuarial leader that centralizes, measures, and adjudicates value-based care contracts at scale. We enable payers and providers to design, measure, and execute value-based agreements with greater transparency, efficiency, and financial predictability. We invest in hiring high potential and humble individuals who thrive in fast-paced environments and can rapidly grow their responsibilities as we continue to accelerate our growth. We were co-founded by Brian Overstreet and Travis May (founder & former CEO of LiveRamp and Datavant, the two biggest data companies of the last 20 years), and are backed by Transformation Capital, Valtruis and other leading investors. In our first 2 years, Arbital Health has established itself as a trusted partner for over 40 payers, providers, and other stakeholders looking to navigate the complexities of risk-based contracting. We are seeking a Product Manager, Data Platform, to own the strategy, roadmap, and execution of Arbital’s data platform – the systems that ingest, process, configure, and serve healthcare claims and contract data for value-based care. You'll define how data flows across the platform – from raw client files through standardized processing, contract configuration, financial reporting, and AI consumption – and partner with engineering, actuarial, and implementation teams to make these systems scalable, configurable, and self-serve so non-engineers can drive day-to-day operations. This is a high-impact individual contributor role for someone who is equally comfortable writing a PRD and digging into a data schema. Responsibilities: Product Strategy & Roadmap Own the product roadmap for Arbital’s data pipeline platform, including ingestion, transformation, calculation, validation, audit trail, and AI consumption layers Define and prioritize pipeline capabilities based on client needs, implementation learnings, engineering constraints, and long-term platform scalability goals Translate complex healthcare data requirements from claims processing to VBC contract logic into structured, buildable product specs Partner with leadership to align pipeline investments with Arbital’s broader product and go-to-market strategy Execution & Delivery Write detailed PRDs, user stories, and technical specifications for platform features, configurations, and automation tooling Work directly with engineering to scope, sequence, and ship pipeline improvements — balancing speed, quality, and flexibility Define acceptance criteria and lead QA processes for new pipeline & platform capabilities, ensuring outputs meet accuracy and performance standards Drive platform delivery end-to-end, owning prioritization, cross-team dependencies, and release coordination Data & Technical Depth Develop deep fluency in Arbital’s data models, pipeline architecture, and healthcare data standards (claims, eligibility, attribution, CMS/ACO files), and actuarial concepts (IBNR, rebates, contract terms) Work hands-on with data — running SQL queries, reviewing pipeline outputs, and validating logic — to inform product decisions and support debugging Define standards for data quality, deduplication, business rule configuration, lineage, and pipeline observability across all client environments Evaluate and recommend tooling improvements across the platform stack (e.g., Airflow, Databricks, AWS) in partnership with engineering Cross-Functional Collaboration Serve as the primary product owner for data capabilities across implementation, engineering, actuarial, and data science teams Partner closely with the Implementation team to surface recurring client configuration needs and turn them into scalable platform features Collaborate with actuarial and data science teams to ensure pipeline logic correctly supports attribution, aggregation, and actuarial use cases Communicate roadmap priorities, tradeoffs, and delivery status clearly to both technical teams and non-technical stakeholders Requirements 4–7 years of experience in product management, with at least 2 years owning data platform, data infrastructure, data pipelines, or platform/API products Strong technical foundation — comfortable reading data schemas, writing SQL, and engaging meaningfully with engineering on architecture decisions Experience working with healthcare data (claims, eligibility, value-based care) strongly preferred Proven ability to translate ambiguous, complex requirements into clear, actionable product specifications Excellent cross-functional collaboration skills — experience working across engineering, data science, and client-facing teams Strong written and verbal communication skills, with an ability to tailor messaging to both technical and business audiences High attention to detail and a strong bias toward quality in data products Comfortable operating with autonomy in a fast-moving, early-stage environment Nice to Have Hands-on experience with Airflow, Databricks, Python, dbt, or AWS data services Background in value-based care, actuarial modeling, or population health analytics Experience building configurable, multi-tenant data pipelines at scale Experience with data lineage, audit trail, or data governance products Prior work at a health tech startup or data-driven healthcare company Familiarity with BI tooling such as Sigma or Looker