DCG is seeking a part-time Quantitative Researcher to support a dynamic team responsible for international survey and consumer behavior research, leveraging experience with statistics, research methods, and data analysis to build, execute, and report on findings across the portfolio.
Requirements
- PhD in biostatistics, statistics, epidemiology, or related quantitative field (or ABD with completion expected within 6 months)
- 1-3 years of post-doctoral experience in applied statistical analysis, or equivalent demonstrated experience through doctoral research
- Proficiency in statistical software (R or SPSS; experience with both preferred)
- Strong foundation in regression analysis and statistical modeling techniques
- Familiarity with project management tools (Teams, SharePoint, etc.)
Responsibilities
- Conduct statistical analyses for international audience research and program evaluation studies, including multivariate regression, propensity score matching, and survey data analysis
- Interpret and synthesize complex statistical outputs (e.g., regression tables, model diagnostics) into clear, accessible summaries for diverse audiences including non-technical government clients
- Prepare analytical sections of research reports, presentations, and deliverables that communicate findings and implications in plain language
- Support quality assurance review of statistical methods and outputs across multiple projects
- Develop statistical analysis plans (SAPs) for research studies
- Conduct data quality checks and validation procedures
- Perform complex statistical analyses (regression, survival analysis, multilevel modeling, etc.)
Other
- Ability to manage multiple concurrent projects and prioritize competing deadlines
- Ability to pass a background check and obtain a Public Trust Clearance
- Location: Although this role is remote, candidates located within the National Capital Region will be given preference
- Travel: Not specified
- Degree requirements: PhD in biostatistics, statistics, epidemiology, or related quantitative field
