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Data Scientist with Security Clearance

Job in Washington, District of Columbia, 20022, USA
Listing for: BOAB Ventures
Full Time position
Listed on 2026-08-23
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, Data Engineering, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Data Scientist / Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions within the Department of Defense’s CDAO ADA IR program. This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands. You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments.

The ideal candidate brings a hybrid of statistical modeling fluency and hands-on software engineering expertise. You will collaborate closely with product managers, full-stack developers, platform engineers, and mission stakeholders to transform raw data into meaningful insights and decision-support tools. This role requires strong technical communication skills, a collaborative mindset, and experience working in agile environments that value reproducibility, testing, and continuous delivery.

Familiarity with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services is highly preferred.

Education and Background

A bachelor's degree plus 3 years of recent specialized experience, OR, an associate's degree plus 7 years of recent specialized experience, OR, a major certification plus 7 years of recent specialized experience, OR, 11 years of recent specialized experience.

Required Skills
  • 4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
  • Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
  • Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, Tensor Flow, XGBoost, MLflow).
Preferred Skills
  • Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
  • Strong understanding of data validation, model testing, and performance evaluation techniques.
  • Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib.
  • Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
Working Conditions

Onsite in a SCIF in the Pentagon.

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