Data Scientist (SME)
About The Position
Peraton is seeking a Data Scientist (SME) to lead the design, development, and operationalization of advanced analytics and machine learning solutions supporting national security and law enforcement missions in support of the CBP analytics and intelligence programs. This role requires deep analytical thinking, machine learning expertise, security awareness, and strong communication skills to translate complex data into mission-impacting intelligence capabilities. The Data Scientist (SME) will operate in a secure, high-assurance environment and collaborate across mission, engineering, and leadership stakeholders to deliver scalable, governed, and operational analytics solutions. Support will be provided across multiple mission locations: Ashburn, VA Sterling, VA Washington, D.C.
Requirements
- Minimum of 8 years with BS/BA. 12 years of experience with a HS diploma/equivalent can be considered lieu of a degree.
- 7+ years of experience in data science or advanced analytics roles.
- Experience supporting CBP or federal law enforcement/intelligence environments.
- Expertise in predictive modeling and advanced analytics.
- Strong proficiency in Python, R, Scala, or Java.
- Advanced SQL skills.
- Experience with big data tools (Spark, Hadoop ecosystem).
- Demonstrated ability to present complex analytics to executive stakeholders.
- Ability to obtain and maintain required CBP BI suitability.
- U.S. Citizenship required.
Nice To Haves
- Bachelors Degree in Data Science, Computer Science, Statistics, Mathematics, Statistics, Engineering or related field (advanced degree preferred).
- Experience deploying ML models into operational environments.
- Experience with NLP, deep learning, or generative AI.
- Familiarity with MLOps tools (MLflow, Kubeflow).
- Relevant analytics or cloud certifications.
Responsibilities
- Lead analysis of large transactional and intelligence datasets to develop predictive, classification, clustering, anomaly detection, and entity resolution models.
- Translate mission challenges into scalable analytic and machine learning solutions.
- Evaluate model performance using statistical validation and performance metrics.
- Extract, clean, and transform structured and unstructured data for analysis.
- Perform exploratory data analysis (EDA) to identify trends, anomalies, and risk indicators.
- Partner with data engineering teams to support scalable data pipelines and distributed processing environments.
- Design, build, and validate machine learning and statistical models.
- Collaborate with engineering and MLOps teams to deploy, monitor, and refine models in production.
- Utilize big data and distributed frameworks such as Spark and Hadoop.
- Develop dashboards and visual analytics to communicate insights clearly.
- Present technical findings and mission impacts to technical teams and senior stakeholders.
- Translate analytical outputs into actionable operational insights.
- Ensure compliance with federal data governance, privacy, and security requirements.
- Document methodologies, validation results, and model limitations.
- Apply ethical AI and bias mitigation practices in model development.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
