Data Scientist

Peraton is seeking a Data Scientist to support the design, development, and deployment of analytical and machine learning components used in customerfacing products and internal proofs of concept (POCs). This role is ideal for someone who can operate independently, learn quickly, and contribute to a fastpaced, exploratory development environment.

In this role, you will:

Lead endtoend analytical solution development, from data exploration through model deployment and performance optimization.
• Direct complex exploratory data analysis (EDA), identifying actionable insights, dataquality risks, and opportunities for new features or modeling approaches.
• Architect and implement advanced statistical and machine learning models, including classical, ensemblebased, and deep learning techniques where appropriate.
• Design scalable, productiongrade feature engineering pipelines and data processing workflows.
• Develop robust prototype data pipelines and collaborate with engineering teams to harden them for production.
• Establish modeling best practices, coding standards, validation frameworks, and experimenttracking methodologies.
• Evaluate emerging techniques, libraries, platforms, and architectures to enhance model performance and product capabilities.
• Create compelling analytical visualizations and presentations for technical and nontechnical stakeholders, translating complex concepts into actionable recommendations.
• Work closely with product managers, engineers, and architects to refine POC concepts, define experiment plans, and integrate analytics into broader product designs.
• Participate in code reviews, knowledgesharing, and crossfunctional collaboration

Basic Qualifications:

• 5 years with BS/BA; 3 years with MS/MA; 0 years with PhD
• Proficiency in Python and common data science libraries (Pandas, NumPy, SciKitLearn, Matplotlib/Seaborn).
• Strong SQL skills and experience with relational or cloudbased data warehouses.
• Understanding of statistical analysis, supervised/unsupervised learning, model evaluation, and feature engineering.
• Experience working with structured and unstructured data, ETL/ELT logic, and basic datapipeline development.
• Familiarity with cloud or containerized environments (AWS, Azure, Databricks, or Docker).
• Ability to build and iterate on ML pipelines, including versioning, reproducibility, and CI/CD concepts (e.g., MLflow, SageMaker Pipelines).
• Skill in producing clear, interpretable, and effective data visualizations.
• Comfortable working through ambiguous or exploratory analytical problems and communicating recommendations clearly.
• Excellent written and verbal communication skills, including stakeholderfacing presentations.
• US Citizenship is required.
• Must have the ability to obtain and maintain a Public Trust clearance.

Preferred Qualifications:

• Databricks experience (Spark, Delta Lake, MLflow)
• Snowflake
• Amazon SageMaker
• Graph databases (e.g., Neo4j)
• Deep learning frameworks (PyTorch, TensorFlow)
• Experience with knowledge graphs or graphbased feature engineering

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.