Lead Data Scientist

Description: Lead applied AI and data science workstreams to improve risk selection, pricing accuracy, and operational efficiency in healthcare. Manage end-to-end delivery of predictive underwriting and pricing models, ensuring alignment with business outcomes and scientific roadmap. Requirements: Bachelor's or master's degree in a quantitative field; advanced degree preferred. 8+ years of experience in data science, machine learning, or actuarial analytics, particularly in healthcare or insurance. Proficiency in Python, SQL, and machine learning frameworks (e.g., scikit-learn, XGBoost). Strong understanding of supervised and unsupervised machine learning methods and MLOps lifecycle. Benefits: Fully paid medical, dental, and vision benefits. Flexible PTO and 401k company contribution. Tuition reimbursement and professional development allowance. Transportation allowance and daily parking reimbursement.