Data Scientist / Data EngineerRole OverviewYou will join a cross-functional product team supporting Government Logistics. The work is hands-on: you will write code, ship models into government production environments, and brief outcomes directly to government stakeholders.
Desired Qualifications- Develop, validate, and deploy statistical and machine learning models to inform supply chain decisions for items managed by Government supply chains (Aviation, Land and Maritime, Troop Support, Energy, Distribution, Disposition Services).
- Design and build data pipelines that integrate authoritative Government systems (EBS / SAP, DSS, EProcurement, FedMall) with external feeds (GIDEP, FPDS-NG, commercial supplier data).
- Translate ambiguous mission questions from senior government leaders into well-scoped analytical problems with measurable outcomes.
- Productionize models within government environments (GCP, AWS GovCloud, Azure Government, on-premise enclaves), meeting DoD RMF, STIG, and IL4/IL5/IL6 controls.
- Document methodology, assumptions, and limitations so government stakeholders - including contracting officers, item managers, and inspectors general - can defend model-informed decisions.
- Support contract deliverables: technical reports, monthly status reports, demonstrations to the COR and government PM, and contributions to white papers and re-compete proposals.
What we are looking for in a strong candidate- Cloud certifications in the area of architecture, data engineering, and/or machine learning
- Background working with government technology projects and programs
- Empathy and Respect: Demonstrated ability to connect with stakeholders, valuing their input, and understanding the nuances of their needs and challenges
Required Qualifications- U.S. citizenship. - Active DoD Secret clearance at time of application. Inactive clearances within the two-year reinstatement window will be considered on a case-by-case basis.
- Bachelor's or higher in a quantitative field - statistics, mathematics, computer science, operations research, industrial engineering, economics, physics, or a closely related discipline. Equivalent experience considered.
- 3+ years (mid-level) or 6+ years (senior) building and shipping data products in a production environment. - Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch or TensorFlow) and SQL. Working knowledge of one of: Spark/PySpark, dbt, Airflow. - Experience with at least one major cloud platform; AWS GovCloud or Azure Government strongly preferred. - Demonstrated experience moving a model from notebook to a monitored production service - including testing, CI/CD, and post-deployment performance tracking. - Experience working with messy, real-world enterprise data (ERP exports, transactional logs, hand-keyed records). - Comfort working in a customer-facing role: explaining technical decisions to non-technical government stakeholders, taking direction from a COR/PM, and operating within the boundaries of the contract scope
Desired Qualifications- Prior contractor experience supporting a Government Customer.
- Familiarity with time-series and intermittent-demand forecasting methods (Croston, TSB, ETS, ARIMA, hierarchical/global deep models such as DeepAR or Temporal Fusion Transformers).
- Experience with operations research techniques: mixed-integer programming, network flow, stochastic optimization (Gurobi, CPLEX, OR-Tools, Pyomo).
- Working knowledge of SAP / ECC / S/4HANA data models, or DLA's Enterprise Business System (EBS).
- Experience operating under DoD RMF, ATO processes, and IL4/IL5/IL6 data handling.
- Familiarity with federal data standards relevant to logistics: NSN/FLIS, NIIN, FSC, UID/IUID, WAWF/iRAPT, DLMS transactions.
- Veterans and transitioning service members with a background in logistics, supply, or acquisition are strongly encouraged to apply.
