Senior Actuary & Data Science Engineer
Summary
A US-based role blending healthcare actuarial science with modern software and data science: designing, validating, and deploying production models (IBNR, risk adjustment, pricing) in Python, R, and SQL, while embedding actuarial judgment into AI systems (generative AI, LLMs) and collaborating with Product and Engineering teams.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Actuary & Data Science Engineer based in United States.
The Senior Actuary & Data Science Engineer will combine deep healthcare actuarial expertise with modern software and data science practices.
Working within a technology organization, you will bridge actuarial science and production engineering to build scalable models that address complex healthcare risk challenges.
You will design and deploy models for areas such as IBNR, financial forecasting, risk adjustment, and pricing.
The role also contributes actuarial expertise to AI systems, helping improve the accuracy, evaluation, and reliability of automated outputs.
You will embed actuarial standards and professional judgment into automated tools and data pipelines while developing rapid prototypes for new approaches.
Close collaboration with Product, Engineering, and Delivery teams will be essential to translating complex healthcare data problems into scalable solutions.
This is an opportunity to expand the impact of traditional actuarial work through technology and help accelerate the adoption of value-based care.
Accountabilities:
- Design, build, validate, and deploy scalable actuarial models, including IBNR, financial forecasting, risk adjustment, pricing, and other healthcare risk models, integrating them directly with platform APIs and engineering pipelines.
- Apply actuarial expertise to complex healthcare data involving areas such as eligibility and claims, transforming real-world data and business challenges into reliable, production-ready solutions.
- Collaborate with Product, Delivery, and Engineering teams to provide actuarial domain context for AI-enabled products, including refining prompts, developing evaluation frameworks, and creating high-quality question-and-answer datasets.
- Help improve the fidelity and effectiveness of automated actuarial outputs by applying professional actuarial judgment and rigorous evaluation practices.
- Embed actuarial governance, professional standards, validation methodologies, and quality controls into automated models, tools, and data pipelines.
- Lead rapid proof-of-concept development to test complex actuarial logic, validate new algorithms, and de-risk technical approaches before broader engineering implementation.
- Translate traditional actuarial methodologies into modern software and data science workflows, identifying opportunities to improve scalability, efficiency, and reproducibility.
- Partner across Product, Engineering, Delivery, and other technical teams to provide technical leadership and communicate complex actuarial concepts clearly to diverse stakeholders.
- Explore emerging technologies and methodologies, including generative AI, LLMs, distributed computing, and cloud data infrastructure, to solve actuarial and healthcare risk problems in innovative ways.
- ASA credential required, with FSA strongly preferred.
- 6+ years of healthcare actuarial experience working extensively with data, including eligibility and claims data, and developing actuarial models.
- Strong hands-on programming skills in Python, R, and SQL, with demonstrated experience producing clean, maintainable, and reproducible code.
- Experience using Git/GitHub for version control and collaborative software development.
- Strong interest in modern technology and demonstrated ability to apply or learn technologies such as generative AI, LLMs, PySpark, and cloud-based data infrastructure.
- Entrepreneurial and highly analytical mindset, with the ability to work effectively in a fast-paced technology environment and take ownership of complex, ambiguous problems.
- Strong communication skills and the ability to explain sophisticated actuarial concepts to Product, Engineering, Delivery, and other non-actuarial stakeholders.
- Hands-on experience with PySpark, Databricks, or distributed computing frameworks is a plus.
- Familiarity with modern AI architectures and evaluation approaches, including RAG, OKF frameworks, or model evaluation suites, is desirable.
- Experience translating traditional actuarial logic into modern engineering languages and production software is highly valued.
- Ability to collaborate effectively across disciplines while balancing actuarial rigor, technical scalability, and practical business needs.
- Annual salary of $190,000–$215,000.
- Generous equity grants through ISO stock options.
- Health, dental, and vision insurance with strong employer-paid contributions.
- 4% 401(k) match.
- Flexible PTO.
- Weeklong winter shutdown.
- 10 paid holidays each year.
- Quarterly team offsites, with occasional travel required.
- Opportunity to work on a critical technology platform supporting the transition toward value-based care in the U.S. healthcare system.
- Collaborative and creative environment with opportunities to learn, build, and take on increasing responsibility.
- Applicants must be legally authorized to work in the United States for the duration of employment.
- This position is not eligible for employer-sponsored immigration sponsorship now or in the future.
Requirements
Benefits
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