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Peraton
Data & Analytics

Data Scientist

Peraton

Full-Time
Lead
$104k – $166k/yr
Virginia
Posted 4d ago

Who can apply

Virginia

The listing asks for applicants in Virginia. Confirm on the employer's page before applying.

Imported Oct 6, 2026 and not yet rechecked against the employer page. Roles can close without notice.

Source: indeed.com

Skills & tools

PythonAWSAzureDockerTensorFlowPyTorchPandasSparkCI/CDSnowflake

Job Description

##### **About Peraton** 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 solve the most daunting challenges that our customers face. Visit peraton.com to learn how we’re keeping people around the world safe and secure. ##### **About The Role** Peraton is seeking a **Data Scientist** to support the design, development, and deployment of analytical and machine learning components used in customer‑facing products and internal proofs of concept (POCs). This role is ideal for someone who can operate independently, learn quickly, and contribute to a fast‑paced, exploratory development environment. **In this role, you will:** * Lead end‑to‑end analytical solution development, from data exploration through model deployment and performance optimization. * Direct complex exploratory data analysis (EDA), identifying actionable insights, data‑quality risks, and opportunities for new features or modeling approaches. * Architect and implement advanced statistical and machine learning models, including classical, ensemble‑based, and deep learning techniques where appropriate. * Design scalable, production‑grade 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 experiment‑tracking methodologies. * Evaluate emerging techniques, libraries, platforms, and architectures to enhance model performance and product capabilities. * Create compelling analytical visualizations and presentations for technical and non‑technical 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, knowledge‑sharing, and cross‑functional collaboration ##### **Qualifications** **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, SciKit‑Learn, Matplotlib/Seaborn). * Strong SQL skills and experience with relational or cloud‑based 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 data‑pipeline 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 stakeholder‑facing 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 graph‑based feature engineering ##### **Details** **Target Salary Range:** $104,000 \- $166,000\. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. **Benefits Statement:** Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits. **Application Statements:** The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. By applying to this job, you are expressing interest in the role and the Company. During the review of your application, you may be required to participate in an on\-camera interview, as well as participate in a process to verify your identity. Use of artificial intelligence (AI) tools of any kind during Peraton interviews is strictly prohibited unless the candidate has obtained prior written authorization. All interview responses must be the candidate’s own. **EEO:** Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.

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