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Statistician / Data Scientist

United States, Suitland · Job Posted February 01, 2026
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Job Description

We are seeking a highly skilled Statistician / Data Scientist with experience working with large and unstructured datasets to support advanced statistical research and model development. This role will focus on predictive modeling, data imputation, model validation, and replication research, while also leading the modernization of analytical workflows through the transition from legacy SAS-based systems to Python-driven data science platforms.

Job Responsibility

  • Lead and support the migration of legacy analytical workflows and models from SAS into cloud ready Python frameworks
  • Translate existing SAS codebases into scalable, maintainable Python pipelines and frameworks
  • Validate equivalency and performance of SAS and Python implementations
  • Develop, test, and validate statistical and predictive models using large, complex, and unstructured datasets
  • Conduct replication research to ensure robustness and reproducibility of models and findings
  • Design and implement advanced imputation strategies for missing or incomplete data
  • Build predictive models for real-world outcomes (e.g., forecasting future residence, income prediction using internal data sources)
  • Apply appropriate methods for complex survey data, including weighting, variance estimation, and uncertainty quantification
  • Collaborate with cross-functional teams to translate analytical outputs into operational and strategic insights
  • Document methodologies, pipelines, assumptions, and results for technical and non-technical audiences

Requirements

  • Degree in Statistics, Data Science, Biostatistics, Economics, or a related quantitative field
  • Experience working with large unstructured datasets
  • Strong background in statistical modeling, predictive analytics, and imputation methods
  • Demonstrated experience with complex survey data and associated estimation techniques
  • Solid understanding of uncertainty quantification and variance estimation
  • Proficiency in Python for data science (e.g., pandas, NumPy, scikit-learn, PyMC, statsmodels)
  • Experience with SAS and modernizing legacy analytical systems into Python environments
  • Experience with model validation, reproducibility, and cross-platform equivalency testing

What we offer

  • generous medical, dental, and vision plans
  • opportunity to work in different sectors
  • remote working opportunities

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