Data Scientist

Looking for an opportunity to make an impact?

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers’ success. We empower our teams, contribute to our communities, and operate sustainably. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. The Leidos Intelligence Sector combines technology-enabled services and mission software capabilities in the areas of cyber, logistics, security operations, and decision analytics to support our defense and intel customers’ mission to defend against evolving threats around the world.

Your greatest work is ahead!

The Intelligence Sector seeks Subject Matter Expert-level Joint Cyberspace professionals to serve within United States Cyber Command (USCYBERCOM).

We have an opening for an experienced Data Scientist. You will architect the frameworks that achieve analytic superiority and actively perform the engineering required to push AI capabilities into production. You are expected to mentor senior technologists by example—working "fingers-on-keyboard" to solve the command's most complex technical roadblocks.

Core Technical Requirements

• Agentic AI Frameworks: Expertise in deploying LangGraph, CrewAI, or AutoGPT to scale network defense at "wire speed."
• Model Engineering: Hands-on fine-tuning of open-source models (Llama 3, Mistral) in air-gapped enclaves using PyTorch or TensorFlow.
• Technical Closing: Direct engineering of Retrieval-Augmented Generation (RAG) stacks using LangChain and vector databases (Milvus or Pinecone).
• Mission Orchestration: Proficiency in unified mission systems (e.g., Kudu Dynamic, TACMS, Maven Support Systems) with custom API integration skills.
• Scripting: Mastery of Python, Go, and Bash.

Preferred Certifications & Experience

• Google Professional ML Engineer, AWS Machine Learning Specialty, or NVIDIA Generative AI/LLM Associate.
• Military Equivalency: CMF Work Role Certification (Exploitation/Network Analyst) or experience as a 170A/17A.

Years of Experience

• Total Experience: 12–15+ years in technical roles.
• AI/ML Focus: 5+ years specifically in Machine Learning Engineering or Data Science. The "Technical Closer" label implies you aren't just managing the project; you are the person who steps in to fix the code when the senior engineers get stuck.
• Domain Expertise: 3–5 years working within the IC/DoD (Intelligence Community/Dept. of Defense) ecosystem, specifically with systems like Maven or TACMS.

Educational Background

• Master’s Degree or PhD in Data Science, Artificial Intelligence, Computer Science, or Mathematics.
• The requirement to fine-tune models (Llama 3, Mistral) using PyTorch/TensorFlow in air-gapped enclaves requires a deep understanding of hardware constraints and model weights that usually comes from advanced academic or special.
• Experience Substitution: A Bachelor’s degree with an additional 5+ years (totaling 15-20) of high-level engineering experience can often substitute for a Master's, especially if backed by the "Military Equivalency" noted in the description.

Clearance Requirement

• TS/SCI with CI Poly required.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

November 4, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $154,050.00 - $278,475.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.