Data Scientist

Leidos is seeking a senior, technical Data Scientist to lead the design, development, deployment, and optimization of advanced data science solutions supporting government mission objectives. This role requires onsite collaboration with mission stakeholders in secure environments.

Key Responsibilities

• Lead the development and operationalization of advanced data science, machine learning, and artificial intelligence solutions for mission applications.
• Design and implement statistical models, predictive analytics, forecasting methods, optimization models, and decision-support tools.
• Extract, transform, integrate, and analyze structured, semi-structured, and unstructured data from multiple government and mission-relevant sources.
• Develop and validate machine learning models for classification, regression, clustering, anomaly detection, ranking, recommendation, and pattern discovery.
• Architect end-to-end analytic workflows, including data ingestion, feature engineering, model training, testing, deployment, monitoring, and lifecycle management.
• Apply advanced quantitative methods to produce actionable insights from large, complex, high-value datasets.
• Collaborate with domain experts, mission analysts, software engineers, and government personnel to translate mission needs into technical solutions.
• Evaluate model performance, quantify uncertainty, and ensure analytic validity, repeatability, and interpretability.
• Support data governance, security, compliance, and responsible AI practices within government mission environments.
• Prepare technical documentation, briefings, reports, white papers, and stakeholder presentations.
• Advise leadership on data science strategy, analytic methodology, capability gaps, and technology insertion opportunities.

Required Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field.
• Minimum of 12–15 years of relevant professional combined experience in data science, advanced analytics, machine learning, artificial intelligence, or statistical modeling.
• Demonstrated experience developing and deploying production-grade analytic or machine learning solutions in government, defense, intelligence, or other highly regulated environments.
• Deep knowledge of statistical inference, probability, experimental design, predictive modeling, and machine learning methods.
• Strong programming experience in Python, R, SQL, or similar analytic languages.
• Experience working with large, complex, and potentially disparate datasets in enterprise environments.
• Familiarity with model validation, explainability, bias assessment, and performance evaluation techniques.
• Strong written and verbal communication skills for explaining complex technical findings to diverse audiences.
• Active TS/SCI with ability to be approved for a Poly.

Technical Skills and Tools

• Statistical modeling and inference; machine learning and artificial intelligence
• Predictive analytics and forecasting; data mining and pattern analysis
• Feature engineering and model evaluation; data wrangling, integration, and transformation
• Python, R, SQL, and scientific computing libraries
• Visualization and dashboarding tools
• Model deployment, monitoring, and lifecycle support
• Documentation, briefing development, and technical communication
• Technologies include: scientific computing libraries; cloud platforms; MLOps; DevSecOps; containerized deployment environments; Spark; Databricks; workflow orchestration tools; deep learning; natural language processing; computer vision; graph analytics; time series analysis; reinforcement learning; distributed computing; data architecture; data engineering; artificial intelligence (AI)

Preferred Qualifications

• Master’s degree or Ph.D. in a relevant quantitative or technical discipline.
• Experience supporting DoD, IC, DHS, civilian federal agencies, or other government mission environments.
• Experience with deep learning, natural language processing, computer vision, graph analytics, time series analysis, or reinforcement learning.
• Familiarity with cloud platforms, MLOps, DevSecOps, and containerized deployment environments.
• Experience with distributed computing, big data platforms (Spark/Databricks or similar), and workflow orchestration tools.
• Familiarity with emerging AI technologies, tools, and methodologies, including their applications, implications, and integration into daily geospatial and intelligence workflows.
• Knowledge of data architecture, data engineering, and enterprise analytics ecosystems.
• Experience briefing senior government leadership and mission stakeholders.

Pay Range

USD 116,350 - 210,325 per year

Location and Work Arrangement

Springfield, VA 22151 (onsite)

Benefits

• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement

Additional Information

• Original posting date: August 6, 2026

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos also considers qualified applicants with criminal histories consistent with relevant laws.

Securing Your Data

Leidos will never ask for payment-related information during the employment application process and will not advance money (such as sending checks or money orders). Communication will be through emails generated by the Leidos.com automated system, not free commercial services or messaging apps. For concerns about fraudulent emails, contact [email protected]. If you believe you are a victim of a scam, contact local law enforcement and report to the U.S. Federal Trade Commission.

U.S. Positions

While subject to change based on business needs, Leidos reasonably anticipates this job requisition will remain open for at least 3 days, with an anticipated close date no earlier than 3 days after the original posting date listed above.