Senior Data Scientist

Are you ready to thrive? Through training, teamwork, and exposure to challenging technical work, let Leidos show how to accelerate your career path.

Join Leidos' all-star team supporting the Defense Intelligence Agency's Enterprise Digital Modernization Accelerator initiative. This program is at the forefront of deploying enterprise-scale AI, data, and mission platform capabilities across cloud, edge, and classified environments. We are looking for creative, driven, and mission-focused professionals ready to take their career to the next level.

As a Senior Data Scientist, you will:

• Lead the design, development, and deployment of advanced analytics and AI/ML solutions for mission-critical applications.
• Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges and deliver innovative, production-ready algorithms and platforms.
• Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics.
• Work with diverse data types (structured, unstructured, open source, digital media) and leverage modern tools such as Python, PyTorch, Scikit-learn, LLM frameworks, and geospatial analytics platforms.
• Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast-paced, engineering-centric environment.
• Enjoy flexible work arrangements, including remote and on-site work in the National Capital Region (Rockville, MD and/or Alexandria, VA).

What You Bring:

• Bachelor's, Master's, or equivalent graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.). Relevant experience may be substituted for a degree.
• 12+ years of experience in data science, analytics, or quantitative intelligence analysis, developing analytics and AI/ML solutions (10+ years with a Master's).
• Active Top Secret clearance and eligibility for TS/SCI with Polygraph.
• Proficiency in Python and at least one other scripting language.
• Demonstrated experience collaborating with hybrid teams to research, build, and deploy complex, user-friendly analytical platforms.
• Track record of creative problem solving, active learning, and mission-focused outcomes.
• Familiarity with version control tools (git, svn, JIRA) and deployment technologies (Docker, Kubernetes, OpenShift).

Preferred Qualifications:

• Experience supporting military or intelligence community customers.
• Expertise with knowledge graphs (neo4j, graph ML), predictive algorithms, image classifiers, object detectors, information retrieval, SQL, Elastic Stack.
• Experience deploying data science applications (e.g., Streamlit) and working with distributed systems (Hadoop, Ray, Spark).
• Familiarity with Azure/C2S, hardware platforms (CPUs, GPUs, FPGAs), and advanced analytical methodologies (social network analysis, supply chain analysis, NLP, classification algorithms, image processing).
• Experience with Large Language Models (LLMs), Multimodal LLMs, Langchain, vLLM, llama.cpp.

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:

June 16, 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 $131,300.00 - $237,350.00

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.