Senior Data and AI Integrator

CACI•Offutt AFB, NE

About The Position

CACI is seeking a Senior Data and AI Integrator to support a mission-focused program advancing national security through data-driven insights, advanced analytics, and innovative technology. The role supports analytical, advisory, and operational capabilities across geographic and functional Combatant Commands, applying data science, statistical analysis, automation, and emerging technologies to challenges in the information environment and irregular warfare mission space. The Senior Data and AI Integrator works with diverse datasets to identify trends, develop analytical models, measure operational effects, and turn complex information into actionable insights for mission partners and senior decision-makers. The position collaborates with intelligence, operations, research, and technology professionals to address evolving global threats. The role requires an active TS/SCI clearance and offers a proposed salary range of $78,000 to $163,800.

Requirements

Active TS/SCI clearance.
Bachelor’s degree in a technical, analytic, or operational discipline.
At least 5 years of experience in software development, data engineering, analytics, or mission system integration.
Hands-on experience with at least one enterprise data platform, such as Foundry, GAIA, AWS/Azure, GCP, or similar.
Demonstrated ability to build or maintain data pipelines, workflows, dashboards, or analytic applications.
Basic AI/ML experience suitable for using tools such as MAVEN’s AI FDE; deep ML research is not required.
Familiarity with OIE, PSYOP, IO, or intelligence operations through training, previous assignments, or adjacent experience.
Ability to convert operational requirements into technical tasks and rapidly produce solutions.
Strong communication skills to coordinate with operators, analysts, and mission partners.

Nice To Haves

At least 2 years of direct experience building or sustaining MAVEN workflows, pipelines, or applications.
Strong proficiency in GAIA and Foundry, especially transformations, routing, ontology usage, and pipeline development.
Advanced full-stack development capabilities, including Python, APIs, data transformation, automation, and integrations.
Ability to design AI-supported workflows using AI FDE to accelerate model creation and analytic output.
Deep operational understanding of PSYOP and OIE requirement generation, planning cycles, and product needs.
Experience integrating analytic tools into mission systems such as MAVEN components, dashboards, or planning platforms.
Track record of leading technical teams in fast-paced operational environments.
Additional certification or training related to data engineering, cloud platforms, or operational analytics.

Responsibilities

Analyze large, complex, and diverse datasets to establish baselines, identify patterns and trends, develop indicators, and support operational decision-making.
Develop and automate analytic workflows using Python, R, and related data science tools to accelerate data discovery, processing, and analysis.
Apply statistical and quantitative techniques, including regression, hypothesis testing, sampling, longitudinal analysis, network analysis, modeling, and reliability and validity assessment.
Develop prototypes, scripts, and analytical tools to improve data collection, processing, integration, visualization, and synthesis.
Apply AI/ML and NLP techniques to structured and unstructured data, including text, survey responses, social media, and operational reporting.
Conduct qualitative and mixed-methods analysis using thematic coding, classification, sentiment analysis, and NLP-assisted analysis.
Develop dashboards, visualizations, and analytical products that communicate complex findings to operational leaders and mission stakeholders.
Integrate analytical findings with intelligence and operational reporting to establish baselines, measure effects, identify emerging trends, and assess OIE/IW activities.
Manage and optimize analytical datasets, databases, metadata, and longitudinal data to support repeatable analysis and research.
Apply geospatial analysis and visualization techniques to assess information environment dynamics, geographic patterns, and audience characteristics.
Use social media and publicly available data with automated collection, analytics, AI/ML, and NLP techniques to evaluate reach, behavior, trends, and operational effects.
Support research and assessment design by developing analytical methodologies, data collection strategies, assessment criteria, and measures of performance and effectiveness.
Collaborate with multidisciplinary teams across intelligence, operations, technology, and research to translate mission requirements into data-driven analytical solutions.