Senior Actuary & Data Science Engineer
New
J
JobgetherHealthcare
Based in United StatesFull-TimeSenior
Salary$190,000–$215,000
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Job Details
- Experience
- 6+ years of healthcare actuarial experience
- Required Skills
- PythonSQLCloud ComputingGitData scienceRGenerative AIPySpark
Requirements
- ASA credential required, with FSA strongly preferred.
- 6+ years of healthcare actuarial experience working with eligibility and claims data.
- Strong hands-on programming skills in Python, R, and SQL.
- Demonstrated experience producing clean, maintainable, and reproducible code.
- Experience using Git/GitHub for version control and collaborative development.
- Demonstrated ability or strong interest in technologies such as generative AI, LLMs, PySpark, and cloud-based data infrastructure.
- Entrepreneurial and highly analytical mindset with the ability to work in a fast-paced environment.
- Strong communication skills for explaining complex actuarial concepts to diverse stakeholders.
- Hands-on experience with PySpark, Databricks, or distributed computing frameworks is a plus.
- Familiarity with modern AI architectures and evaluation approaches, including RAG and model evaluation suites, is desirable.
Responsibilities
- Design, build, validate, and deploy scalable actuarial models, including IBNR, financial forecasting, risk adjustment, pricing, and other healthcare risk models.
- Apply actuarial expertise to complex healthcare data involving eligibility and claims to create production-ready solutions.
- Collaborate with Product, Delivery, and Engineering teams to provide actuarial domain context for AI-enabled products.
- Improve the fidelity and effectiveness of automated actuarial outputs using professional judgment and rigorous evaluation.
- Embed actuarial governance, professional standards, and quality controls into automated models and data pipelines.
- Lead rapid proof-of-concept development to test complex actuarial logic and validate new algorithms.
- Translate traditional actuarial methodologies into modern software and data science workflows.
- Partner across cross-functional teams to provide technical leadership and communicate actuarial concepts to non-actuarial stakeholders.
- Explore emerging technologies including generative AI, LLMs, distributed computing, and cloud data infrastructure.
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