Sourcing - Assistant Director, Advanced Analytics: Workforce Planning

Description 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. What you'll do: Strategy & Framework Development

• 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

Staffing and Forecast Redesign based on effort

• 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

Operationalization & Governance

• 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.
• *This role may have in-office requirements depending on candidate location**

Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote. The ideal candidate will have:

• Bachelor's Degree plus a minimum of 10 years, typically 8 or more years of experience, or equivalent, is required. Industrial engineering background is preferred.
• Advanced knowledge of data sources, tools, statistical principles and methodologies, and techniques.

Qualifications

• 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.

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