Data Scientist (Applied AI – Performance Management)

Summary

Leidos is seeking an Applied Data Scientist to support a large, mission-critical Navy program through its Performance Management team. The role applies data science and AI to operational datasets to identify performance improvement opportunities, improve POAM effectiveness, and enable proactive, code-first performance management.

Responsibilities

• Apply data science and AI techniques to large, complex operational datasets to identify performance degradation, systemic issues, and improvement opportunities
• Design and implement code-first analyses and models that support automated or semi-automated performance opportunity discovery
• Use AI and advanced analytics to evaluate, prioritize, and improve the effectiveness of POAMs tied to contractual performance outcomes
• Work collaboratively with performance analysts, engineers, and stakeholders to translate operational problems into data-driven solutions
• Explore and apply context-appropriate AI techniques, balancing innovation with explainability and defensibility
• Build reusable analytical approaches, code, and methods that elevate the team’s overall capability in data science and AI
• Communicate insights clearly and credibly to technical and non-technical stakeholders, including leadership
• Support broader Navy performance initiatives (e.g., WAM) by extending methods and insights beyond SLR-focused use cases where appropriate

Skills

• Bachelors and 4 – 8 years of prior relevant experience or Masters with 2 – 6 years of prior relevant experience. Additional years of experience may be accepted in lieu of a degree
• US citizenship with the ability to obtain and maintain an active DoD Secret security clearance
• Experience applying data science, machine learning, or AI to real-world operational or performance problems
• Strong problem-framing skills: ability to understand ambiguous problems, identify relevant data, and determine appropriate analytical approaches
• Proficiency in Python or similar languages for data analysis and modeling
• Experience working with large, messy, or heterogeneous datasets
• Ability to explain complex analytical results clearly and defensibly
• Collaborative mindset and comfort working as part of a multidisciplinary team
• Experience with applied machine learning, statistical modeling, or AI techniques used for pattern detection, prioritization, or forecasting
• Familiarity with operational performance metrics, service-level agreements, or contract-driven environments
• Experience balancing advanced methods with explainability and stakeholder trust
• Exposure to AI enablement, platform thinking, or reusable analytics frameworks
• Experience supporting large-scale or enterprise environments

Qualifications

Must Haves

• Bachelors and 4 – 8 years of prior relevant experience or Masters with 2 – 6 years of prior relevant experience. Additional years of experience may be accepted in lieu of a degree
• US citizenship with the ability to obtain and maintain an active DoD Secret security clearance
• Experience applying data science, machine learning, or AI to real-world operational or performance problems
• Strong problem-framing skills: ability to understand ambiguous problems, identify relevant data, and determine appropriate analytical approaches
• Proficiency in Python or similar languages for data analysis and modeling
• Experience working with large, messy, or heterogeneous datasets
• Ability to explain complex analytical results clearly and defensibly
• Collaborative mindset and comfort working as part of a multidisciplinary team

Nice to Haves

• Experience with applied machine learning, statistical modeling, or AI techniques used for pattern detection, prioritization, or forecasting
• Familiarity with operational performance metrics, service-level agreements, or contract-driven environments
• Experience balancing advanced methods with explainability and stakeholder trust
• Exposure to AI enablement, platform thinking, or reusable analytics frameworks
• Experience supporting large-scale or enterprise environments

Benefits

• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement
• Remote work