All-Source Intelligence Data Scientist

Overview

As an All-Source Intelligence Data Scientist, you fuse multi-INT data to build analytical models, automate data pipelines, and surface decision-ready insights for senior leaders. You collaborate with intelligence professionals to translate requirements into repeatable, data-driven workflows and develop models that reveal patterns of life. You create intuitive visualizations to accelerate sense-making and support operational decision-making within a mission-driven team. This role offers meaningful impact by applying data science to national security missions.

Pay / Benefits

• health benefits
• life insurance
• disability benefits
• retirement benefits
• paid leave
• tuition assistance

Responsibilities

• Elicit analytic questions from stakeholders and translate them into technical requirements and backlogs within agile processes
• Design end-to-end data solutions: ingestion from collection systems, schema design, ETL, model training/evaluation, and operational delivery
• Develop statistical and machine learning models for entity resolution, anomaly detection, classification, clustering, and pattern-of-life analysis across multi-INT datasets
• Build dashboards and lightweight apps to communicate insights, assessments, and confidence levels to varied audiences
• Guide teammates, set technical standards, and evolve analytic tradecraft using modern data ecosystems

Key requirements

• 5+ years in data science across structured and unstructured sources
• Proficiency in Python and SQL or R, with Pandas/NumPy, scikit-learn, and model evaluation/tuning
• Experience building ETL pipelines and querying APIs with Airflow or dbt, and Git version control
• Experience developing predictive models and quantitative analyses for intelligence assessments
• Experience applying NLP or text mining to reporting and open-source content
• Experience integrating multi-INT data (SIGINT, HUMINT, GEOINT, OSINT, MASINT) and conducting pattern-of-life analysis
• Ability to synthesize narrative and quantitative findings
• Active TS/SCI clearance; willingness to take a polygraph
• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Data Analytics
• Stakeholder engagement
• Clear communication
• Collaborative teamwork
• Python
• SQL or R
• Pandas

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