Lead Data Scientist

Job Summary

To drive measurable improvements in risk selection and pricing accuracy, the full-time remote Lead Data Scientist will independently manage applied AI and data science workstreams, overseeing the entire process from problem framing to model deployment and performance monitoring.

Key Responsibilities:

• Own end-to-end delivery and measurable outcomes for predictive underwriting and pricing workstreams, ensuring alignment on model quality and operational efficiency
• Define and document data requirements, ensuring high data quality and readiness for analytics across various data sources
• Develop, validate, and deploy predictive models while championing best practices in explainability, model governance, and performance monitoring

Required Qualifications:

• Bachelor's or master's degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, or a related quantitative field; an advanced degree is a plus
• 8+ years of experience in data science, machine learning, or actuarial analytics, with a focus on healthcare or insurance risk
• Advanced proficiency in Python and SQL, with experience in machine learning frameworks such as scikit-learn and XGBoost
• Proven experience managing production models and the MLOps lifecycle on cloud platforms like AWS
• Strong business acumen with the ability to connect analytical outputs to measurable business outcomes