Build and deploy scalable healthcare actuarial models within production software and AI systems. The role involves actuarial governance, model validation, data pipeline integration, AI evaluation, rapid prototyping, and technical collaboration with Product, Engineering, and Delivery teams. Candidates must translate complex healthcare risk and claims data problems into reproducible software solutions using Python, R, and SQL.
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.
The Opportunity
We are seeking an experienced, credentialed actuary (ASA or FSA) with a passion for software and modern technology to join us as Senior Actuary & Data Science Engineer.
Unlike traditional actuarial roles, this position sits directly within our Technology Organization. You will serve as the bridge between complex actuarial science and production software—building scalable actuarial models, integrating them within our AI architecture, embedding actuarial professionalism into automated tools, and creatively solving traditional healthcare risk problems using novel and emerging practices.
If you are an actuary who wants to build models at scale to increase their impact and to revolutionize value-based care and the actuarial practice through technology, this role is built for you.
What you'll do:
● Production Model Engineering: Design, build, and deploy scalable actuarial models (e.g., IBNR, financial forecasting, risk adjustment, pricing, etc.) that plug directly into our platform APIs and core engineering pipelines to solve real and complex actuarial problems.
● AI Context & Efficacy: Collaborate with Product, Delivery, and other Engineering teams to inform domain context for our Arbital AI suite—refining prompts, expanding evaluation frameworks (e.g., CADRE), providing Golden question/answer pairs, and ensuring high fidelity in automated actuarial outputs.
● Actuarial Governance & Standards: Embed rigorous actuarial best practices, professionalism, and validation standards directly into our automated modeling tools and data pipelines.
● Domain-Driven Prototyping: Lead rapid proof-of-concept (POC) builds to de-risk complex actuarial logic and test new algorithmic approaches before working with other engineering teams to apply technical scaling.
● Cross-Functional Technical Leadership: Partner closely with Product, Engineering, and Delivery teams to translate messy real-world healthcare data problems into clean, scalable software solutions.
● AI Context & Efficacy: Collaborate with Product, Delivery, and other Engineering teams to inform domain context for our Arbital AI suite—refining prompts, expanding evaluation frameworks (e.g., CADRE), providing Golden question/answer pairs, and ensuring high fidelity in automated actuarial outputs.
● Actuarial Governance & Standards: Embed rigorous actuarial best practices, professionalism, and validation standards directly into our automated modeling tools and data pipelines.
● Domain-Driven Prototyping: Lead rapid proof-of-concept (POC) builds to de-risk complex actuarial logic and test new algorithmic approaches before working with other engineering teams to apply technical scaling.
● Cross-Functional Technical Leadership: Partner closely with Product, Engineering, and Delivery teams to translate messy real-world healthcare data problems into clean, scalable software solutions.
What you bring:
● Credentials: Associate of the Society of Actuaries (ASA) required; Fellow of the Society of Actuaries (FSA) preferred.
● Experience: 6+ years of healthcare actuarial experience working with data (e.g., eligibility and claims) and building models.
● Technical Proficiency: Strong hands-on coding skills in Python, R, and SQL, with a demonstrated history of writing clean and reproducible code.
● Engineering Mindset: Experience with Git/GitHub for version control and collaborative development.
● Modern Tech Curiosity: Deep interest or experience in leveraging modern technology—such as generative AI, LLMs, PySpark, or cloud data infrastructure—to solve complex actuarial or data science problems.
● Problem Solver: Entrepreneurial mindset with the ability to thrive in a fast-paced technology organization and communicate complex actuarial concepts to other teams.
● Experience: 6+ years of healthcare actuarial experience working with data (e.g., eligibility and claims) and building models.
● Technical Proficiency: Strong hands-on coding skills in Python, R, and SQL, with a demonstrated history of writing clean and reproducible code.
● Engineering Mindset: Experience with Git/GitHub for version control and collaborative development.
● Modern Tech Curiosity: Deep interest or experience in leveraging modern technology—such as generative AI, LLMs, PySpark, or cloud data infrastructure—to solve complex actuarial or data science problems.
● Problem Solver: Entrepreneurial mindset with the ability to thrive in a fast-paced technology organization and communicate complex actuarial concepts to other teams.
Bonus points for:
● Hands-on experience with PySpark, Databricks, or distributed computing frameworks.
● Familiarity with modern AI architectures (e.g., RAG or OKF frameworks, model evaluation suites).
● Experience translating traditional actuarial logic into modern engineering languages.
● Familiarity with modern AI architectures (e.g., RAG or OKF frameworks, model evaluation suites).
● Experience translating traditional actuarial logic into modern engineering languages.
Why Join Us?
We are assembling a team of creative, talented visionaries seeking to build a new technology that will change healthcare. You will be able to learn, build, and scale our team and technology in a collaborative, creative culture that values every team member.
We Offer:
• Generous equity grants of ISO stock options
• We offer an exceptional benefits package with high employer-paid contributions for health, dental, and vision insurance
• 4% 401(k) match
• Flexible PTO, a weeklong winter shutdown, and 10 holidays each year
• Occasional travel required - Quarterly team offsites
• The opportunity to build a critical software platform that accelerates the American healthcare system's transition to value-based care
Work Authorization
• Applicants must be legally authorized to work in the United States for the duration of their employment.
• This position is not eligible for employer-sponsored immigration sponsorship, now or in the future. • Applicants must be able to work in the United States without requiring employer sponsorship.
• Applicants must be legally authorized to work in the United States for the duration of their employment.
• This position is not eligible for employer-sponsored immigration sponsorship, now or in the future. • Applicants must be able to work in the United States without requiring employer sponsorship.
Similar Jobs
Fintech • Financial Services
Lead the design and execution of global total rewards programs, including compensation bands, benefits strategy, equity and incentive plans, job leveling, pay equity, and annual compensation cycles. Advise executives, HR business partners, and talent acquisition using market data, financial modeling, and internal equity analysis. Optimize total rewards systems and programs across a growing global organization.
Top Skills:
CandoriqPavePayscaleRippling
Healthtech
Build and maintain Customer Success and Implementation playbooks, SOPs, training programs, knowledge bases, presentation materials, and scalable workflows. Partner cross-functionally to communicate process and product changes, improve automation and efficiency, identify customer risks, and measure enablement effectiveness. Support implementation, launch readiness, customer health, escalations, business reviews, renewals, and expansion.
Top Skills:
NotionSalesforce
AdTech • Digital Media • Marketing Tech • Mobile
Own full-cycle global recruiting for technical, product, sales, business, and operational roles. Source and evaluate candidates, advise hiring managers, manage interview processes, and maintain hiring momentum. Oversee recruiting vendors and a global sales consultant program, including contracts, onboarding, CRM tracking, documentation, and follow-up. The role requires independent judgment, strong communication, business acumen, discretion, and experience working across time zones in a distributed company.
Top Skills:
CRM
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
