Data Scientist (5076)

SMX•Stafford, VA

17h•$145,000 - $195,000

About The Position

The Data Scientist supports our customer’s mission priorities by developing predictive models, analytical solutions, and data-driven insights that directly enable AI use cases such as investigations support, risk detection, and operational intelligence. This role focuses on applied machine learning, statistical modeling, and advanced analytics to transform mission and operational data into actionable intelligence, while partnering closely with data engineers, cloud engineers, and mission subject matter experts.

Requirements

3–5 years of hands-on data engineering experience.
10+ years of technical professional experience.
Experience developing machine learning and statistical models in applied environments
Strong proficiency with Python and common data science libraries (e.g., pandas, scikit-learn, PyTorch, TensorFlow, or equivalent)
Experience performing exploratory data analysis and feature engineering
Experience building data visualizations and analytical products for decision support
Experience working with structured and unstructured data sources
Ability to communicate analytical results clearly to non-technical stakeholders
Experience supporting projects with data governance, privacy, or compliance considerations

Nice To Haves

Experience with risk analytics, investigations, or operational intelligence use cases
Familiarity with responsible AI practices, model governance, and explainability techniques
Experience working with cloud-based data science or AI platforms (e.g., Azure ML or similar)
Experience collaborating in agile or iterative delivery environments
MuleSoft implementation experience.

Responsibilities

Develop and validate predictive and statistical models supporting mission use cases
Design and execute exploratory data analysis to identify patterns, risks, and opportunities
Build machine learning models to support investigations, vetting, and mission risk intelligence
Create analytical features and training datasets in coordination with data engineers
Evaluate model performance, bias, and explainability for mission and governance needs
Develop visualizations and analytical products to communicate results to stakeholders
Support AI solution pilots and MVPs through rapid experimentation and iteration
Collaborate with governance and cybersecurity teams to ensure responsible and compliant analytics