
Posted 22 days ago
Senior Actuary & Data Science Engineer
AI Summary
Builds and deploys scalable actuarial models within a healthcare technology platform, integrating them with AI systems and engineering pipelines to solve value-based care risk problems.
About this role
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:
● 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:
● 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:
● Familiarity with modern AI architectures (e.g., RAG or OKF frameworks, model evaluation suites).
● Experience translating traditional actuarial logic into modern engineering languages.
Skills
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