● 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.