Lead WC Modeling: Serve as the model owner for Workers’ Compensation predictive models, ensuring alignment with pricing and business priorities.
Partner on strategic vision while managing team capacity and driving timely model deliverables.
Model Development & Deployment: Lead design, maintenance, and deployment of predictive models for frequency, severity, and loss cost estimates, ensuring production readiness and effective integration into pricing workflows.
Cross-Functional Collaboration: Partner with Actuarial, Data Engineering, Underwriting, and Product teams to connect modeling initiatives with pricing strategies and organizational goals, promoting shared problem-solving.
Innovation: Drive modernization through advanced modeling techniques, machine learning, and AI to enhance efficiency and decision-making.
Lead experimentation with new data sources, features, and methodologies to uncover insights and advance strategic objectives.
Operational Excellence: Ensure robust documentation, validation, and governance, along with scalable processes to monitor model performance and maintain reliability.
Talent Development: Mentor and develop team members, fostering a culture of curiosity, ownership, and continuous learning.
Support hiring and onboarding, including intern and actuarial student rotations.
Strategic Influence: Participate in enterprise initiatives to ensure Workers' Compensation predictive models are efficiently integrated into core data and system platforms.

Requirements

8+ years of relevant analytical experience
Master’s or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or a relevant professional designation (e.g. FCAS, FSA, CSPA, ACAS, ASA)
Expertise in statistical modeling, inference, and building machine learning algorithms in Python and/or R
Expertise in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation.
Experience in SQL and familiarity with cloud-native environments (e.g., Snowflake, Sagemaker).
Able to communicate effectively with both technical and non-technical audiences.
Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution.
Prior Management Experience Highly Preferred

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

statistical modelingmachine learningPythonRSQLdata validationmodel developmentpredictive modelingdata analysismodel performance monitoring

communicationmentoringteam managementproblem-solvingstrategic thinkingcollaborationcuriosityownershipcontinuous learninginfluence

FCASFSACSPAACASASAMaster’s degreePh.D.