Assistant Director, Data Science, Capacity Modeling

Assistant Director, Data Science, Capacity Modeling

Join to apply for the Assistant Director, Data Science, Capacity Modeling role at Liberty Mutual Insurance
. This position is part of the Capacity Modeling and Optimization team within Claims and Service Data Science, building advanced forecasting and staffing optimization models.

• Apply advanced analytics to step/click level and other operational data to model claim/exposure durations and action frequencies; build stochastic models that capture variability and drivers.
• Develop clustering/segmentation strategies for claims and exposures; design statistically rigorous tests to evaluate efficiency gains and service impacts.
• Build simulation models to compare assignment policies; quantify throughput, cycle time, and quality tradeoffs; create the mathematical case for recommendations.
• Create work effort-based demand forecasts and staffing models; solve allocation and scheduling problems using mathematical optimization; deliver scenario analyses for planners.
• Build and maintain data pipelines and automated quality checks; maximize usable data via censoring aware methods, imputation, and reconciliation across sources.
• Follow MLOps best practices to produce reproducible code, versioned experiments, and monitored models; collaborate with engineering to operationalize datasets, dashboards, and services.
• Provide technical mentorship, communicate findings to diverse stakeholders, and contribute to cross functional initiatives and best practices.

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Expert knowledge of predictive toolset; reflects as expert resource for tool development.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
• Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU.
• Ability to give effective training and presentations to peers, management and less senior business leaders.
• Ability to use results of analysis to persuade team or department management to a particular course of action.
• Has a value driven perspective with regard to understanding of work context and impact.
• Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 2 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 4 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and a minimum of 5+ years of relevant experience.

• Strong foundation in statistical modeling and inference, including hierarchical/Bayesian methods, survival/censoring analysis, GLM/GAM, time series forecasting, and experimental design/causal inference.
• Expertise in operations research and simulation: discrete event or agent-based simulation, queueing theory, and optimization (linear/mixed integer programming).
• Proficiency in Python and SQL; experience with data manipulation and modeling libraries (pandas, Num Py, scikit learn, stats models; PyMC a plus) and OR tools (Pyomo or OR Tools); familiarity with Sim Py or similar simulation frameworks.
• Experience building production data pipelines and applying MLOps practices (Git, CI/CD, experiment tracking such as MLflow) and workflow orchestration (e.g., Airflow).
• Ability to translate analytics into operational recommendations and influence decision making in partnership with Claims, Service, and Workforce Management.
• Track record of moving models from prototype to production and measuring impact through experiments or counterfactual analysis.

• Knowledge of claims and service operations, exposure level modeling, and workforce management practices.
• Experience with cloud platforms (AWS preferred), distributed data processing (Spark), and dashboarding/visualization tools.
• Familiarity with reinforcement learning or bandit methods for dynamic routing or assignment.

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