Operational Energy Data Analyst

• Bachelors’ degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field, with 4+ years of data analysis experience or a Masters’ degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field, with 3+ years of data analysis experience.\n
• Active DOD Secret security clearance.\n
• Proficiency across data manipulation, analytics, and governance tools (e.g., SQL, Python, PySpark, Databricks, ETL pipelines, Power Automate, and Tableau/PowerBI/Qlik).\n
• Proven experience designing scalable data architectures and developing rigorous statistical analytics frameworks.\n
• Demonstrated track record in technical writing with strong verbal and written communication skills across technical and executive audiences.\n
• Ability to travel as business needs require.\n, * Familiarity with or direct experience supporting the Air Force Operational Energy or related DoD energy initiatives.\n
• Hands-on experience developing data pipelines, models, or workflows within Palantir Foundry.\n
• Demonstrated experience developing and deploying deep learning or machine learning models using frameworks such as PyTorch or TensorFlow.\n

The Leidos team supporting the Deputy Assistant Secretary of the Air Force for Operational Energy has an opening for an Operational Energy Data Analyst. Leidos supports the Deputy Assistant Secretary of the Air Force (Operational Energy) (SAF/IEN) with project management and policy support subject matter experts. Each year about $9B, or 7-8% of the Air Force budget has gone to purchase energy. Approximately 86%, or $7.2B, is operational energy (aviation fuel). The Air Force Operational Energy Program vision is to create an energy optimized Air Force that maximizes combat capability for the warfighter\n \n Location: This is a remote position; however, candidates must reside in the Washington, DC metropolitan area.\n \n Primary Responsibilities:\n \n \n

• Collaborate with the Operational Energy team to quantify the impact of prospective and current initiatives using statistical analysis, data wrangling, and predictive machine learning models.\n
• Establish key performance indicators (KPIs) to track and evaluate the effectiveness of team projects and initiatives.\n
• Design, build, and maintain interactive business intelligence dashboards focused on fuel consumption and aviation energy data.\n
• Define and evaluate aviation energy metrics to identify and prioritize actionable energy-saving opportunities.\n
• Acquire and validate necessary aviation operational data, conducting quantitative analyses to recommend optimal energy-efficiency solutions.\n
• Maintain regular, proactive communication with cross-functional stakeholders and team liaisons.\n

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