Assistant Director, Advanced Analytics: Workforce Planning

Liberty Mutual Insurance•Boston, MA

19h•Remote

About The Position

Join the Workforce Planning (WFP) organization within US Retail Markets (USRM) Claims & Service where you’ll provide strategic analysis and support to the Claims & Service organization, delivering recommendations that span long-term claims and call volume forecasts, staffing and hiring needs, and partner strategy, all the way to day-to-day management of our internal and external resources. As an Assistant Director, Advanced Analytics on the Work Effort Assessment team, you will play a critical part in optimizing our staffing models and workload management strategies using data-driven insights and process analytics. The ideal candidate has experience in not only developing a framework and strategy for managing a complex capability but also executes on cross-team implementation of identified recommendations. We are seeking someone with experience in Claims process data collection that can execute on cross organization initiatives. This role will operationalize complex, multi-stakeholder studies using intelligent tools that gather big data to identify operational improvements and efficiency gains. You will not directly manage a team of analysts, but you will lead through expertise, structured thinking, and executive-level communication. The models you help design will be built by data science and analytics engineering partners; your role is to own the strategy, framework, and architecture of the transition.

Requirements

Bachelor's Degree plus a minimum of 10 years, typically 8 or more years of experience, or equivalent, is required.
Advanced knowledge of data sources, tools, statistical principles and methodologies, and techniques.
Master's Degree in Mathematics, Economics, Statistics or any other quantitative field plus a minimum 5 years of applied business / non-academic experience preferred.
For non-Master s Degree candidates, Bachelor's Degree and minimum of 7 years of applied business/non-academic experience, or equivalent.
Proven track record of developing and applying modeling to business problems.
Deep knowledge of data sources, tools and business drivers.
Ability to apply more advanced analytical concepts to improve business outcomes.
Advanced proficiency in Excel (VBA, macros, scripts, formulas, data visualization, etc.), PowerPoint, and statistical software packages (SAS, Emblem).
Must have good planning, analytical, decision-making and communication skills.

Nice To Haves

Industrial engineering background is preferred.

Responsibilities

Assess overall design and structure of broader projects and provide insights and recommendations on enhancement opportunities. Define what “good” looks like.
Lead the design of a complexity-based claims classification framework, defining tiers, complexity drivers, and governance processes for how claims are categorized and re-evaluated over time
Develop the methodology for transitioning staffing models from stick-count-based productivity assumptions to work-effort-adjusted capacity models that reflect true time-on-task variation across claim types and complexity levels
Partner with volume forecasting and data science teams to redesign demand forecasting at a more granular level — by claim type, complexity tier, channel, and line of business — to serve as the upstream input to work-effort-based staffing
Design or evaluate approaches to ongoing time-on-task measurement (e.g., system log analysis, work item metadata, structured time studies) to keep standards current as products, processes, and claim mixes evolve
Ensure staffing strategy and model logic align with broader USRM Claims goals and account for expected shifts in volume, mix and complexity
With LOB process and analytics teams, partner on improvement initiatives focused on redundancies and automation opportunities and perform detailed process variation and outlier analysis to pinpoint inefficiencies
Develop and maintain standardized metrics, benchmarking frameworks, and reporting structures across studies
Meets with supervisor to discuss project status and present recommendations, performs special projects as requested.