Senior Operations Data Analyst

Capital I•Frederick, MD

3d•Onsite

About The Position

Serves as a senior advisor to Army Medicine leadership, translating operational needs into data-driven insights, dashboards, and decision-support tools. Leads development of analytics products, ensures data quality, and applies advanced analysis to improve operational performance, readiness, and efficiency across Army/DOD environments.

Requirements

Active Secret clearance.
Bachelor’s degree in related field of study
10 years of experience with Army logistics
Proficiency with Microsoft Office, including Word, Excel, PowerPoint, and Power BI
Experience defining KPIs, operational metrics, and executive reporting
Experience performing data validation, reconciliation, cleaning, and root-cause analysis
Strong ability to translate ambiguous business problems into analytic questions, data requirements, and usable products
Ability to manage multiple priorities, shifting requirements, and tight deadlines in a client-facing environment
Experience developing interactive dashboards and visualizations in Power BI or similar BI platforms
Experience working in Army and/or DOD network environments with associated access, security, and deployment constraints
Experience briefing or supporting senior military/civilian leaders
Experience with SQL, data querying, and data transformation
Knowledge of data governance, access controls, and cybersecurity constraints in government environments
Must provide documentation of eligibility to legally work in the United States without an employer sponsored visa.
Must be able to pass background screening.

Nice To Haves

inventory management and SSA/warehouse data operations
Familiarity with Palantir Foundry/Advana and SAP modules to include but not limited to Financial and Accounting and Controlling, Sales and Distribution, Materials Management, and Plant Maintenance, and other authoritative systems of record
Knowledge of Army logistics, medical logistics, sustainment, and supply chain operations
Experience supporting development and operationalization of AI/ML-enabled analytic tools in approved environments
Experience with forecasting, anomaly detection, demand planning, inventory optimization, readiness analysis, or process improvement

Responsibilities

Serves as a trusted advisor to Army Medicine senior leaders by translating operational questions into analytic approaches, dashboards, and decision-support tools.
Provide quality assurance reviews of relevant products developed by more junior Data Analysts.
Designs, builds, maintains, and enhances operational dashboards, KPIs, scorecards, and decision-support products in Army-approved platforms such as Power BI, Army Vantage, and other Army enterprise analytics environments.
Conducts organizational studies, evaluations, and operational assessments.
Gathers, validates, and organizes information related to operational problems, process inefficiencies, and improvement opportunities.
Applies mathematical modeling, statistical analysis, and optimization methods to support decision-making, policy formulation, and other managerial functions.
Defines and monitors performance metrics to assess operational effectiveness, efficiency, readiness, and compliance.
Develops studies and recommendations related to new systems, procedures, and organizational changes to improve operations.
Presents findings and recommendations to management through executive briefings, presentations, and written reports.
Collaborates with functional SMEs, technical teams, and government stakeholders to ensure solutions are feasible, secure, and sustainable within Army/DOD network environments.
Supports user acceptance testing, deployment, training, and adoption of dashboards and tools; develops SOPs, user guides, and data dictionaries.
Performs data validation, reconciliation, cleaning, and root-cause analysis to improve data quality and trust in decision-support products.
Supports development and operationalization of AI/ML-enabled analytic tools, where authorized, to improve forecasting, anomaly detection, and operational decision-making.