AI Data Scientist

Leidos•Chantilly, VA

16h

About The Position

Leidos is seeking a hands-on AI Data Scientist to develop modern training, education, and mission-support applications for national security programs. The role combines applied data science, AI/ML integration, and software engineering to build scalable, interactive learning and training systems in classified environments. It is an individual-contributor role focused on execution and delivery, with daily production coding and work across the application stack. The position works with instructional designers, software engineers, mission stakeholders, analysts, and UX teams to create intelligent, data-driven learning platforms and operational training tools. The successful candidate will build modern web-based applications, especially with TypeScript and contemporary front-end frameworks, and integrate AI/ML and data science capabilities into operational training systems. The work covers the full software development lifecycle, from architecture and implementation through testing, deployment, and sustainment. The role also uses AI-assisted development tools and coding agents while maintaining strong standards for code quality, security, maintainability, and testing. The position requires an active TS/SCI clearance with Polygraph. The stated pay range is $131,300 to $237,350. Leidos notes that the range is a general guideline and not a guarantee of compensation.

Requirements

Bachelor’s degree in Computer Science, Data Science, Software Engineering, Mathematics, Engineering, or a related technical field with 12+ years of relevant experience, or a master’s degree with 10+ years of experience; additional experience may be considered in lieu of a degree.
Strong hands-on software engineering experience with TypeScript and modern front-end development.
Experience with modern front-end frameworks such as React, Next.js, Angular, or Vue.
Practical experience applying data science, analytics, or AI/ML techniques to real-world applications.
Proficiency in Python and familiarity with common data science and machine learning libraries.
Experience integrating applications with APIs, backend systems, and data services.
Familiarity with AI/ML workflows, including data preparation, model integration, inference pipelines, or analytics processing.
Experience using modern AI-assisted software development tools and coding agents in professional engineering workflows.
Familiarity with AI coding ecosystems and developer productivity tools such as Claude Code, OpenAI Codex, Cursor, OpenCode, GitHub Copilot, or similar platforms.
Ability to leverage AI-assisted development while maintaining sound software engineering fundamentals, debugging practices, testing discipline, and secure coding standards.
Strong understanding of modern software development practices, including Git, CI/CD, automated testing, and agile methodologies.
Ability to independently design and implement production-ready technical solutions.
Strong analytical, troubleshooting, and problem-solving skills.
Strong written and verbal communication skills.
Must hold an active TS/SCI clearance with Polygraph.

Nice To Haves

Experience supporting training, education, simulation, or learning technology environments.
Experience building intelligent tutoring systems, adaptive learning platforms, or analytics-driven training applications.
Experience with large language models (LLMs), generative AI, NLP, or AI-assisted user experiences.
Familiarity with AI frameworks and ecosystems such as Hugging Face, LangChain, vector databases, or agentic AI frameworks.
Experience developing applications using agentic or AI-accelerated software engineering workflows.
Familiarity with AI-enabled developer tooling integrated into modern IDEs, terminals, and CI/CD environments.
Experience evaluating, customizing, or operationalizing AI coding agents for enterprise or mission-focused development environments.
Experience combining AI-assisted development with modern TypeScript, React, or full-stack application architectures.
Experience with data visualization, interactive analytics, or dashboard development.
Experience with learning ecosystems or standards such as SCORM, xAPI, or LMS integrations.
Familiarity with Node.js or full-stack application development.
Experience deploying applications in cloud or enterprise environments.
Experience modernizing legacy applications into modern web architectures.
Experience supporting Department of Defense, Intelligence Community, or national security customers.

Responsibilities

Design, develop, and maintain modern web-based training and learning applications.
Build responsive, scalable, and accessible front-end applications using TypeScript and modern frameworks.
Develop and integrate AI/ML-enabled capabilities into training and operational support systems.
Apply data science and analytics to adaptive learning, user insights, performance analysis, and mission workflows.
Collaborate with instructional designers and subject matter experts to translate learning objectives into interactive digital experiences.
Integrate front-end systems with APIs, backend services, AI/ML pipelines, and enterprise platforms.
Develop reusable UI components, visualizations, and workflows for scalable training ecosystems.
Work with structured and unstructured data sources across enterprise and classified environments.
Participate in the full software development lifecycle, including architecture, implementation, testing, deployment, and sustainment.
Support deployment and operationalization of AI/ML capabilities within production systems.
Use AI-assisted development workflows and coding agents for software delivery, prototyping, testing, refactoring, and documentation.
Apply contemporary engineering practices using AI-powered development tools while maintaining code quality, security, maintainability, and testing standards.
Evaluate and integrate emerging developer tooling and agentic engineering capabilities into team workflows and application development practices.
Troubleshoot application, integration, and data-related issues across distributed environments.
Contribute to software engineering standards, reusable frameworks, and development best practices.
Stay current with emerging front-end, AI/ML, and learning technology trends.