Data Science, Advisor

Peraton•,

2d•$112,000 - $179,000•Remote

About The Position

Peraton is seeking a Senior Data Science Engineer to support the design, development, integration, and optimization of cloud-based data and artificial intelligence (AI) solutions supporting defense mission systems. This is a 100% remote position within the United States, with occasional travel to client sites as required. The ideal candidate combines strong data science and software engineering skills with hands-on experience implementing AWS cloud services, data pipelines, analytics, and AI/ML solutions in secure environments.

Requirements

Bachelor’s degree with 8 years of relevant experience; or Master’s degree with 6 years of relevant experience; or Doctorate with 3 years of relevant experience; or 12 years of relevant experience in lieu of a degree
Ability to obtain and maintain a DoD Secret security clearance. U.S. citizenship is required to obtain a security clearance
Degree or professional experience in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related technical field
Hands-on experience designing and implementing scalable cloud-based data platforms and solutions
Experience with AWS cloud services, particularly data, analytics, AI, and machine learning services
Programming experience with one or more of the following: Python, SQL, Rust, or TypeScript
Experience with database schema design, data modeling, and software engineering best practices
Demonstrated ability to independently learn new technologies, troubleshoot complex technical issues, and develop effective solutions
Strong analytical, problem-solving, technical documentation, and communication skills

Nice To Haves

Experience with Amazon Bedrock, SageMaker, Glue, QuickSight, and Macie
Experience developing or integrating generative AI and LLM-based applications
Experience working with DoD, federal, or other highly regulated environments
Familiarity with CUI, NIST, RMF, and cloud security requirements
Experience designing secure, highly available, and scalable AWS architectures
AWS certifications such as AI Practitioner, Solutions Architect, Developer, Data Engineer, Machine Learning, or Generative AI Developer

Responsibilities

Design, develop, and integrate Amazon Web Services (AWS) data, analytics, AI, and machine learning services into client applications and mission systems.
Analyze and document client database schemas, data flows, and data architectures to identify opportunities for AI/ML integration and automation.
Develop analytics and reporting dashboards using Amazon QuickSight to provide actionable insights to technical and leadership audiences.
Leverage Amazon Bedrock to develop, integrate, and deploy Large Language Model (LLM) capabilities and generative AI solutions.
Design, develop, and optimize ETL/ELT data pipelines using AWS Glue and related cloud services.
Implement Amazon Macie and other AWS security capabilities to identify and protect Personally Identifiable Information (PII) and sensitive data.
Use Amazon SageMaker to prepare, transform, and manage data supporting downstream analytics and machine learning workflows.
Implement and enforce Controlled Unclassified Information (CUI) handling requirements, data protection measures, and applicable security controls.
Apply data engineering, software development, and cloud architecture best practices to build scalable, reliable, and maintainable solutions.
Support technical activities across the program and identify opportunities for continuous improvement, automation, innovation, and operational efficiency.
Assess technical risks, develop solution alternatives, and communicate architectural decisions and recommendations to program and client leadership.
Collaborate with software engineers, data scientists, system architects, cybersecurity professionals, and mission stakeholders to deliver integrated solutions.