Data Scientist (Group 4), Senior

Job Title: Data Scientist (Group 4), Senior Job Category: Engineering Time Type: Full time Minimum Clearance Required to Start: TS/SCI Employee Type: Regular Percentage of Travel Required: Up to 10% Type of Travel: Local * * * The Opportunity: CACI is currently seeking a Data Scientist II in support of a program whose initiative is aimed at combating evolving and emerging threats, supporting related exploitation and replication activities, and advancing operational rehearsal, exercise, wargaming, and counter system development. Additionally, we are focusing on integration and experimentation, including Modeling and Simulation. By joining this team, you will have a unique opportunity to contribute to the U.S. and our allies’ ability to develop and apply models and simulations throughout the lifecycle of military and commercial technologies and systems. Your work will help ensure Warfighter readiness and the realization of future capabilities.

: • Lead Advanced Data Analysis & Management: Execute the full data lifecycle, including acquiring, processing, and interpreting large, disparate datasets (structured, unstructured, and natural language) to extract actionable insights for DoD modeling and simulation programs • AI and Simulation Integration: Design and develop data-driven solutions for M&S and AI systems, including creating and refining generative AI analysis workflows and ensuring data integrity for complex simulations • Custom Analytics & Tool Development: Build custom analytical pipelines, models, and tooling to meet advanced and emerging data

, particularly with high-volume, real-time data feeds • Technical Leadership: Execute and lead project tasks, manage technical complexity, conduct code reviews, and ensure the quality of analytical output across a team or mission set • DoD M&S Domain Expertise: Apply deep domain knowledge to military operations and exercises, with familiarity with DoD M&S environments and toolsets (e.g., JLVC, JTLS-GO) to translate data into meaningful analytical conclusions • Big Data Ecosystem Management: Support data ecosystem development capable of handling big data, large complex data sets, and manage data storage archives of recorded test events, training activities, and exercises • AI/ML Development: Provide advanced data science and data analytics tools, software, algorithm, and analysis support including application of artificial intelligence (AI), machine learning (ML), and digital engineering to simulation data sets