Data Scientist with Security Clearance

BOAB Ventures; Washington (District of Columbia); On-site; USD 120,000 - 180,000; Full time

Job summary

BOAB Ventures seeks a Data Scientist/Engineer to design, develop, and operationalize scalable, AI-enabled data solutions within the DoD’s CDAO ADA IR program. You will build data pipelines, feature engineering strategies, and ML services in secure, containerized environments, collaborating with product managers, developers, and mission stakeholders.

The ideal candidate combines statistical modeling with hands-on software engineering, and thrives in agile settings that value reproducibility,

Qualifications

• 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, TensorFlow, XGBoost, MLflow).

Responsibilities

• Design, develop, and deploy scalable AI-enabled data solutions for DoD environments.
• Build and optimize data pipelines, pre-processing, feature engineering, and ML services.
• Collaborate with product managers, developers, and stakeholders in agile, reproducible workflows.
• Work in secure, containerized environments (SCIF) and ensure mission-critical reliability.

Skills

Python

SQL

Spark/Databricks

ML deployment

MLflow

MLOps

API development

AWS

Azure

Data visualization

Communication

Education

Bachelor's degree

Associate's degree

Major certification

Tools

Spark

Databricks

TensorFlow

PyTorch

MLflow

Tableau

Plotly

Matplotlib

Palantir Foundry

Job description

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, TensorFlow, 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.