Senior Statistician

Integrated Business & Technical Consultants • Vienna, VA

2d • Hybrid

About The Position

IBTCI seeks a Senior Statistician for an anticipated multi-year Clearinghouse for Labor Evaluation and Research (CLEAR) project funded by the U.S. Department of Labor (DOL) Chief Evaluation Office (CEO). The position is contingent upon contract award and is a consultancy estimated at 800 hours per year under a BPA schedule. The role is the principal quantitative and statistical authority for the CLEAR project, overseeing advanced meta-analytic models, effect-size computations, attrition calculations, quantitative descriptive guidelines, and statistical audits across evidence review streams.

The position is based in Washington, DC / Vienna, VA, with hybrid or remote work. Work may be conducted at the contractor’s office or remotely. This is a sedentary office position involving extended computer screen time, analytical programming, and virtual technical meetings. The role supervises statistical analysts and quantitative research assistants on analytical subtasks and may require limited domestic travel for in-person DOL technical briefings or Technical Working Group workshops. The position reports to the Principal Investigator / Project Director.

Requirements

• At least 10 years of advanced professional experience in applied statistics, biostatistics, econometrics, or quantitative social science research, specializing in evaluation design and synthesis.
• Demonstrated experience executing advanced meta-analyses, hierarchical linear modeling (HLM), meta-regressions, and econometric causal-inference techniques.
• Fluency in attrition, baseline equivalence, clustering adjustments, and regression-discontinuity checks.
• Advanced computational proficiency with statistical software such as R, Stata, Python, or SAS, including scripting reproducible analytical workflows.
• Ph.D. in Statistics, Biostatistics, Econometrics, Quantitative Psychology, or a related quantitative field; alternatively, a master’s degree in a quantitative discipline with at least 10 years of relevant statistical evaluation experience.
• Ability to lift up to 20 lbs.

Nice To Haves

• What Works Clearinghouse certified reviewer preferred.
• Familiarity with evidence-clearinghouse statistical standards such as CLEAR, What Works Clearinghouse Version 4.1/5.0 standards, and Campbell Collaboration.
• Familiarity with emerging applications of natural language processing (NLP), machine learning, or large language models to evidence synthesis and systematic reviews.

Responsibilities

• Provide high-level statistical direction for CLEAR evidence review projects and resolve complex statistical challenges involving clustering, baseline equivalence, missing-data imputation, unit-of-analysis issues, and multiple-comparison corrections.
• Lead and conduct advanced statistical meta-analyses, meta-regressions, and core components analyses across pooled labor evaluation datasets to assess intervention effectiveness, subgroup variations, and effect moderators.
• Develop and standardize algorithms, code scripts, and calculators for standardizing effect sizes, including Hedges' g, odds ratios, and Cox proportional hazards coefficients, across diverse econometric and psychometric study specifications.
• Collaborate with the Principal Investigator and DOL CEO to maintain and update CLEAR’s Quantitative Descriptive Guidelines, Causal Evidence Guidelines, and Regression Discontinuity Design standards.
• Establish validation protocols for verifying attrition thresholds, differential attrition models, and covariate balance requirements under CLEAR standards.
• Support exploratory pilots applying machine learning and AI models, such as text mining, automated screening classifiers, and data-extraction algorithms, to streamline CLEAR review pipelines.
• Interface with external Technical Working Groups and DOL statisticians to defend methodological rating criteria, adjudicate disputed study scores, and draft technical methodology memos.
• Supervise statistical analysts and quantitative research assistants on analytical subtasks.
• Travel domestically as needed for in-person DOL technical briefings or Technical Working Group workshops.

What This Job Offers

• Career Level: Senior
• Education Level: Ph.D. or professional degree