Note: The job is a remote job and is open to candidates in USA. D&G Solutions is seeking a part-time Data Scientist to support logistics and operational mission analysis. The role develops statistically defensible representations of logistics-network behavior, fits probability distributions, builds and evaluates statistical or predictive models, analyzes simulation outputs, and communicates uncertainty and findings for decision support.
Responsibilities
- Perform exploratory data analysis to characterize distributions, variability, correlations, outliers, missingness, seasonality, and other patterns in logistics and operational data
- Fit and validate probability distributions for key network variables and quantify uncertainty using statistical methods, sensitivity analysis, resampling, and Monte Carlo techniques
- Develop and evaluate statistical and predictive models, including classification, clustering, and anomaly detection, to improve understanding of logistics-system behavior and support mission decisions
- Assess data sufficiency, model assumptions, performance, and uncertainty to distinguish meaningful signals from noise and identify additional data needs
- Partner with Operations Research Analysts to translate 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, collaborating with Data Engineers, Database Architects, and Logistics SMEs to validate analytical fitness
- Translate results into decision-ready visualizations and findings, and document methods, assumptions, code, diagnostics, limitations, and data provenance to support reproducibility and government delivery
Skills
- Bachelor's degree from an accredited university in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Engineering, Economics, or a related quantitative field
- 8+ years of experience applying statistics, probability, data science, or predictive analytics to complex operational or mission problems
- Strong foundation in 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
- Demonstrated experience performing exploratory analysis, fitting distributions, evaluating statistical models, Monte Carlo techniques, and communicating analytical findings to technical and non-technical audiences
- Experience working with modeling and simulation, operations research, logistics analytics, or other stochastic analytical environments
- Remote
- 10% Travel to client site in Washington, D.C. as needed
- Must be a U.S. citizen and able to attain a security clearance
- This role is restricted to U.S. person(s) (U.S. citizens, permanent residents, and other protected individuals under 8 U.S.C. 1324b(a)(3))
- 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
Benefits
- Remote work
- 401(k)
- Bonus and profit sharing
- Flexible hours
- Education reimbursement
- PTO
Company Overview