Arbital 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 Technical Implementation Manager to lead the onboarding of new clients and ensure successful deployment of Arbital’s platform. This role is critical to our growth and bridges product, actuarial, sciences and engineering teams. You’ll work directly with customer stakeholders and internal teams to drive implementations from contract intake through data ingestion, validation, pipeline execution, adjudication, and production deployment - owning the technical configuration, QA process, and client experience.
Lead implementation projects from signed contract to go-live, executing scope, timelines, and deliverables Translate complex value-based care contract requirements into technical platform configurations Define and oversee client-specific data ingestion strategies, including secure transfer setup (SFTP), file structures, mapping approaches, and delivery cadence Partner with engineering and actuarial teams to confirm ingestion requirements (eligibility, claims, reference files) and run initial ingestion tests Work with client teams to ensure data is delivered in the expected format, complete, and on time; escalate gaps or issues with clear remediation paths Run or coordinate data quality checks (missing fields, control totals, coverage periods, attribution completeness) Translate customer requirements into structured technical specs across intake, data preparation, adjudication build, and production release Manage project timelines and coordinate with delivery, engineering, and actuarial teams to resolve escalations Oversee ingestion and validation of healthcare datasets (claims, eligibility, CMS/ACO files, attribution/engagement data) Collaborate with engineering to define, configure, and validate data pipeline outputs - including business rules such as deduplication, attribution, and aggregation logic - that drive Arbital’s core modules Oversee adjudication and platform reporting setup, ensuring data and calculations align with customer contracts Validate staging environments and outputs across Arbital’s platform modules, leading the sign-off process to confirm accuracy and readiness for launch Act as the bridge between technical and business stakeholders, translating requirements into execution and outputs into insights Communicate progress, risks, and decisions clearly to both clients and internal leadership Provide technical guidance during customer training, walkthroughs, and early adoption Continuously refine the implementation flow by surfacing opportunities for product improvements, process automation, and new tooling to drive scalability and efficiency
3–5 years of experience in SaaS product implementation, healthcare data analytics, or client delivery (data-driven products preferred) Strong ability to translate complex contracts and datasets into structured implementation steps and requirements Familiarity with healthcare data (claims, eligibility, value-based care/actuarial data) strongly preferred Proven experience managing cross-functional workstreams (engineering, product, science, delivery) Strong organizational skills, with ability to manage multiple implementations in parallel High level of attention to detail Excellent communication skills, both client-facing and internal Comfort with technical workflows (data pipelines, configs, SQL/Python/R, BI tools such as Sigma)
Startup experience is highly preferred Experience with Airflow, Databricks, Python, and AWS Business logic development coding in R/Python VBC experience