Data Scientist with Security Clearance

R
- Description Leidos is actively interviewing for a Data Scientist to join our team in Springfield, VA.

Job Summary Senior-most technical position responsible for leading the design, development, deployment, and optimization of advanced data science solutions in support of government mission objectives. The Data Scientist serves as a recognized subject matter expert in statistical modeling, machine learning, artificial intelligence, data exploitation, and analytic tradecraft. This role requires on-site support at a government facility and close collaboration with mission operators, analysts, engineers, program leadership, and government 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 derive actionable insights from large, complex, and 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 Technical Skills
* 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 Basic 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 with the ability to explain complex technical findings to diverse audiences.
* Active TS/SCI with ability to be approved for a Poly

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.
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