Data Scientist: DoD AI & Data Pipelines (Onsite)

Agile Defense, LLC; Colorado Springs (CO); On-site; USD 120,000 - 180,000; Full time

Job summary

Agile Defense, LLC invites a Data Scientist to support design, development, and deployment of AI-enabled data solutions within defense programs. The role focuses on building scalable data pipelines, feature engineering, and ML services in secure environments, partnering with product teams and engineers to deliver decision-support tools.

The ideal candidate has strong Python/SQL skills, experience with Spark/Databricks, and a track record in ML model deployment, within an agile, teamwork-driven

Qualifications

• Bachelor’s degree or higher plus 3 years of specialized experience, OR an associate’s degree plus 7 years of specialized experience, OR major certification plus 7 years of specialized experience, OR 11 years of specialized experience.
• 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).

Responsibilities

• Design, develop, and deploy scalable AI-enabled data solutions for Department of Defense programs.
• Build data pipelines, pre-processing workflows, and feature engineering strategies.
• Collaborate with product managers, developers, and mission stakeholders to deliver actionable insights.

Skills

Data science

ML engineering

Data pipelines

Education

Bachelor’s degree or higher + experience

Tools

Spark

Databricks

PySpark

scikit-learn

TensorFlow

XGBoost

MLflow

Tableau

Job description

Agile Defense, LLC invites a Data Scientist to support design, development, and deployment of AI-enabled data solutions within defense programs. The role focuses on building scalable data pipelines, feature engineering, and ML services in secure environments, partnering with product teams and engineers to deliver decision-support tools.

The ideal candidate has strong Python/SQL skills, experience with Spark/Databricks, and a track record in ML model deployment, within an agile, teamwork-driven