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# Data Scientist / Data Engineer

- **Company:** GAME PLAN TECH LLC
- **Location:** Washington, DC, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Microsoft Azure, Business Systems, Cloud Computing, Computer Programming, Continuous Integration, IBM ILOG CPLEX Optimization Studio (CPLEX), Information Engineering, Data Governance, E-Procurement, Integer Programming, Python (Programming Language), Machine Learning, SAP ERP, NumPy, Tensorflow, SAP (Applications), SQL Databases, Data Processing, Cloud Platform System, Pytorch, Apache Spark, Pandas, Build Management, Pyspark, Scikit Learn, Information Technology, SAP S/4HANA, Data Pipelines
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-scientist-data-engineer-dc--3d350b03-5b3a-40a4-a8dd-341747164bb0

## About the Role

Data Science, Production Systems, Logistics, Government, Computer Programming, Cross-Functional, Product Support, Aviation Industry, Machine Learning, Supply Chain, * 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, * 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, * 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.

## Description

* 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.