Data Scientist

D&G Support Services, LLC is hiring a part-time Data Scientist to support remote, statistically grounded work in logistics-network modeling, simulation, and decision support. The role centers on creating representations of logistics behavior that are defensible through rigorous analysis, uncertainty quantification, and clear documentation for reproducible government delivery.

As part of a multidisciplinary team, you will focus on statistical analysis and predictive modeling, working alongside Operations Research Analysts and other stakeholders to translate empirical findings into stochastic inputs and parameters used in modeling and simulation.

Responsibilities

• Conduct exploratory data analysis to characterize distributions, variability, correlations, outliers, missingness, seasonality, and other patterns across logistics and operational data.
• Fit and validate probability distributions for key network variables, quantifying uncertainty using statistical methods, sensitivity analysis, resampling, and Monte Carlo techniques.
• Build and assess statistical and predictive models (classification, clustering, and anomaly detection) to improve understanding of logistics-system behavior and inform mission decisions.
• Evaluate data sufficiency, model assumptions, performance, and uncertainty to separate meaningful signal from noise and identify additional data needs.
• Collaborate with Operations Research Analysts to convert empirical findings and probability distributions into defensible stochastic inputs, parameters, and assumptions for modeling and simulation.
• Analyze simulation outputs for variability, confidence, convergence, sensitivity, and statistical significance, partnering with Data Engineers, Database Architects, and Logistics SMEs to validate analytical fitness.
• Translate results into decision-ready visualizations and findings, documenting methods, assumptions, code, diagnostics, limitations, and data provenance to support reproducibility and government delivery.

Requirements

• Bachelor’s degree from an accredited university in a related quantitative field: Data Science, Statistics, Mathematics, Operations Research, Computer Science, Engineering, Economics, or a similar discipline.
• 8+ years of experience applying statistics, probability, data science, or predictive analytics to complex operational or mission problems.
• Strong knowledge of probability distributions, statistical inference, hypothesis testing, regression, uncertainty quantification, and model validation.
• Proficiency in Python and SQL, including practical use of common scientific and statistical analysis libraries.
• Experience conducting exploratory analysis, fitting distributions, evaluating statistical models, running Monte Carlo techniques, and communicating findings to technical and non-technical audiences.
• Experience in modeling and simulation, operations research, logistics analytics, or other stochastic analytical environments.

Technologies

• Python
• SQL

Benefits

• Competitive salary
• Benefits
• 401(k)
• Bonus and profit sharing
• Flexible hours
• Education reimbursement
• PTO

Location

• Remote
• 10% travel to client site in Washington, D.C. as needed

Clearance and Eligibility

• Must be a U.S. citizen and able to attain a security clearance.
• Restricted to U.S. person(s) (U.S. citizens, permanent residents, and other protected individuals under 8 U.S.C. 1324b(a)(3)).

Preferred

• Master’s degree or Ph.D. in Statistics, Data Science, Operations Research, Applied Mathematics, Engineering, or a related quantitative field.
• Experience with Bayesian analysis, survival/reliability analysis, time-series analysis, or other techniques relevant to logistics-network uncertainty.
• Experience supporting Federal Government or Department of War modeling, simulation, analytics, or decision-support programs using logistics, transportation, aviation, cargo, UAS, operational-energy, or other mission-performance data.