Senior Statistician

Department Institutional Support/Program Implementation (ISPI)

Integrated Business & Technical Consultants, Inc. (IBTCI), a U.S. based international development consulting company established in 1987, has worked in over 100 countries and implemented over 300 projects. IBTCI serves government agencies, private sector companies, and several donor agencies. IBTCI specializes in monitoring, evaluation, research, and learning (MERL) and institutional support across many areas and sectors including, but not limited to, conflict and crisis, democracy and governance, agriculture, economic growth, food security, education, environment, and global health.

Location:

Washington, DC / Vienna, VA (Hybrid / Remote)

Type:
Consultancy (Estimated 800 hours/year under BPA Schedule)

Classification:
Consultant

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.

The Senior Statistician serves as the principal quantitative and statistical authority on the CLEAR project, responsible for overseeing advanced meta-analytic models, effect size computations, attrition calculations, quantitative descriptive guidelines, and statistical audits across all evidence review streams.

Provide high-level statistical direction for CLEAR evidence review projects, resolving complex statistical challenges concerning 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 (e.g., Hedges' g, odds ratios, Cox proportional hazards coefficients) across diverse econometric and psychometric study specifications.

Collaborate with the PI and DOL CEO to maintain and update CLEAR's Quantitative Descriptive Guidelines, Causal Evidence Guidelines, and Regression Discontinuity Design (RDD) standards.

Establish validation protocols for verifying attrition thresholds, differential attrition models, and covariate balance requirements under CLEAR standards.

and support exploratory pilots applying machine learning and AI models (e.g., text mining, automated screening classifiers, data extraction algorithms) to streamline CLEAR review pipelines.

Interface with external Technical Working Groups (TWG) and DOL statisticians to defend methodological rating criteria, adjudicate disputed study scores, and draft technical methodology memos.

A minimum of ten(10) years of advanced professional experience in applied statistics, biostatistics, econometrics, or quantitative social science research, specializing in evaluation design and synthesis.

Demonstrated track record of 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;
What Works Clearinghouse certified reviewer preferred.

Familiarity with evidence clearinghouse statistical standards (e.g., CLEAR, What Works Clearinghouse Version 4.1/5.0 standards, Campbell Collaboration).

Advanced computational proficiency using statistical software packages (R, Stata, Python, or SAS), including scripting reproducible…