Lead Analyst – Quantitative Social Science Research

Location: RemoteEmployment Type: Contract / Project-BasedAnticipated Period: October 2026 – September 2027Company: The Brandon Green Management Group (BGMG)Project: Federal Correctional Officer Retention Analysis

Position Summary

BGMG is seeking is seeking a Lead Analyst to lead quantitative analysis for a federal workforce research project examining correctional officer attrition and monetary retention incentives.This role is pending subject to contract award

The Lead Analyst will lead statistical analysis using R, including regression analysis and quasi-experimental designs (QEDs). The work is expected to include discrete-time survival analysis and staggered difference-in-differences analysis. The analyst must be able to assess model assumptions, adjust analytic methods when needed, document code, and explain complex findings in plain language.

Key Responsibilities

• Serve as technical lead for quantitative research and statistical analysis.
• Refine and expand government-provided analysis plans.
• Conduct descriptive analysis of correctional officer attrition using workforce and payroll data covering 2001–2026.
• Examine how attrition risk changes over an employee's career.
• Analyze individual and institution-level factors associated with attrition.
• Conduct discrete-time survival analysis, including logistic regression where appropriate.
• Analyze relationships between monetary retention incentives and attrition.
• Conduct staggered difference-in-differences or other appropriate quasi-experimental analyses.
• Examine dose-response relationships between incentive levels and attrition.
• Assess interactions involving institution characteristics such as rurality and security level.
• Evaluate model assumptions and adjust statistical methods when supported by the data.
• Conduct sensitivity, diagnostic, and robustness analyses as appropriate.
• Write clean, documented, reproducible R code.
• Prepare shareable R code that allows DOJ to replicate analyses.
• Interpret statistical results and limitations.
• Draft technical findings for interim and final reports.
• Translate complex quantitative results into concise, plain-language findings for decision makers.
• Support development of presentation materials for non-technical audiences.
• Provide technical leadership to supporting researchers and analysts.

The solicitation places specific emphasis on deep quantitative expertise and the ability to adjust analytic techniques based on the available data rather than simply executing a predetermined model.

Minimum Qualifications

Candidates must meet one of the following education paths:

• Doctor of Philosophy (Ph.D.) in statistics, economics, or another quantitative social science from an accredited institution; or
• Master’s degree in statistics, economics, or another quantitative social science plus three additional years of related professional experience above the minimum requirement.

Candidates must also have:

• At least 5 years of professional experience in applied quantitative social science research.
• Expertise writing R code.
• Experience implementing regression analyses in the context of quasi-experimental designs.
• Experience serving as a team leader.
• Experience translating complex quantitative findings into plain-language, concise findings.

Preferred Qualifications

• Workforce or labor research experience.
• Difference-in-differences analysis experience.
• Survival or event-history analysis experience.
• Experience analyzing longitudinal workforce, payroll, or administrative data.
• Experience with non-random treatment assignment and observational research designs.
• Experience with U.S. Government-funded research.
• Experience preparing reproducible analytical code and documentation.
• Experience presenting statistical findings to non-technical decision makers.

Application Requirements

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