Data Scientist - Mid-Level

Overview

The Data Scientist enables advanced analytics and data-driven decision-making across the Joint Intelligence Operations Center (JIOC). This role applies scientific, statistical, and computational techniques to process, structure, and analyze large volumes of multi-source intelligence data. The Data Scientist builds and deploys AI/ML models, advanced automation solutions, and predictive analytics capabilities that enhance intelligence processes, strengthen situational awareness, and directly support operational planning and critical warfighting functions.

This position requires strong quantitative skills, experience with large and complex datasets, and the ability to collaborate with analysts, engineers, and mission partners to develop high-impact solutions that drive intelligence insight and operational advantage.

Responsibilities

• Perform complex statistical analysis, modeling, and data mining to extract actionable insights from diverse intelligence datasets.

• Design, develop, and implement advanced data visualizations to support all aspects of JIOC intelligence operations.

• Build and validate statistical and predictive models to identify trends, patterns, and relationships across multi-INT sources.

• Develop and contribute to AI/ML algorithms, automation workflows, and intelligent systems that enhance mission effectiveness.

• Conduct exploratory data analysis across internal and external datasets to support analytic findings and operational planning.

• Create automated processes for data ingestion, conditioning, and integration to streamline intelligence production.

• Collaborate with intelligence analysts, data engineers, and computer scientists to improve data workflows and develop new analytical capabilities.

• Develop algorithms, scripts, and tools to automate manual processes and enhance analytic efficiency.

• Improve data quality, searchability, metadata structures, and predictive capabilities across intelligence repositories.

• Apply experimental design principles to test hypotheses and evaluate intelligence processes.

• Recommend improvements to data architectures, workflows, and analytic capabilities across the enterprise.

• Conduct system analyses to define technical requirements for new or enhanced intelligence databases and applications.

• Identify data redundancies, gaps, and inefficiencies and develop solutions to optimize integration and accessibility.

• Participate in intelligence planning conferences, capability development sessions, working groups, national-level coordination boards, and technical exchange meetings.