Advanced Analytics Lead, Strategic Modeling (Atlanta)

Advanced Analytics Lead, Strategic Modeling

At Morgan & Morgan, the work we do matters. For millions of Americans, we're their last line of defense against insurance companies, large corporations or defective goods. From attorneys in all 50 states, to client support staff, creative marketing to operations teams, every member of our firm has a key role to play in the winning fight for consumer rights. Our over 6,000 employees are all united by one mission : For the People.

We're building the analytics engine that powers strategic decision-making for America's largest personal injury firm. This role involves building, maintaining, and evolving case-level forecasting models that drive headcount planning, revenue & P&L projections, and prescriptive recommendations. You'll partner with leadership across operations, finance, and legal to translate data into staffing plans, financial outlooks, and actionable targets using SQL, Python, Excel, Power BI. This position will be a part of the Strategy & Insights group.

Core Responsibilities

Develop & Own Forecasting Models : Build and continually tune drivers-based case progression and settlement forecasts that feed into attorney / staff headcount models, revenue projections, and P&L scenarios.

Headcount & Capacity Planning : Translate case inventory and flow forecasts into staffing needs (attorneys, case managers, support), including what-if scenario modeling (growth, attrition, rightsizing) and pipeline management.

Revenue & P&L Modeling : Integrate forecasted case outcomes, fee structures, and timing lags into multi-period financial models to project cash flow, revenue recognition, profitability, and marketing ROI.

Prescriptive Analytics : Surface actionable recommendations (e.g., staffing reallocation, marketing spend adjustments, operations bottlenecks) based on deviations and leading indicators.

Dashboarding & Automation : Build and maintain automated dashboards / reports (Power BI + SQL, Excel, Python pipelines) to surface forecast outputs, variance analyses, KPIs, and scenario comparisons to stakeholders.

Cross-functional Partnership : Work closely with Operations, Finance, and Marketing to align assumptions, socialize forecasts, and embed analytic insights into planning cycles.

Benchmarking & Goal Setting : Establish internal benchmarks (e.g., case resolution velocity, attorney productivity, budgeting) and help set realistic targets.

Root Cause & Variance Analysis : Lead deep dives when actuals diverge from forecast; quantify driver impacts and recommend corrective actions.

Influence & Storytelling : Provide the Strategy & Insights group with concise narratives and presentations to report to senior leadership for driving strategic decisions.

Strategy & Insights : Provide timely, data-backed insights on special initiatives, one-off questions, and evolving business needs across multiple cross functional groups.

Qualifications

Must-Haves :

Bachelor's degree in computer science, engineering, statistics or related field.

4+ years of hands-on experience in data science, analytics, forecasting, or BI with proven ownership of models that influenced staffing / revenue decisions.

Deep proficiency in SQL for exploring and transforming large operational datasets.

Proficient in Python or R with hands-on experience in data processing, statistical modeling, automation, and machine learning (e.g., pandas, NumPy, ML libraries, or equivalent).

Experience building interactive dashboards / reports, with an emphasis on best practices data modeling (Power BI strongly preferred).

Strong Excel modeling skills.

Demonstrated ability to translate data into business impact, translating findings to a non-technical audience.

Familiarity with drivers-based and bottom-up forecast construction, variance analysis, and scenario planning.

Comfortable working with ambiguity, juggling multiple planning cycles, and delivering under tight timelines.

Excellent communication skills : ability to document and socialize assumptions, methodologies, and results.

Nice-to-Haves :

Prior experience in legal operations, personal injury or litigation-focused forecasting, or professional services staffing models.

Exposure to P&L modeling with lag structures (e.g., case lifecycle revenue recognition).

Experience with prescriptive analytics / optimization (simple decision rules, cost-benefit tradeoffs).

Familiarity with statistical survival analysis, competing risks, time series, causal inference, and specialized time-to-event modeling (common in case progression).

Experience integrating data from CRM / Case management systems (e.g., Litify / Salesforce) into forecasting pipelines.

Knowledge of revenue operations (RevOps) concepts and how they intersect with capacity and cost models.

Experience with statistical tools.

Experience building interactive internal tools.