Data Scientist Applied AI Performance Management

Data Scientist Applied AI Performance Management at Leidos

Leidos is seeking a Data Scientist Applied AI Performance Management to support a large, mission-critical U.S. Navy program. This role supports a Performance Management team focused on improving contractual and operational performance through the applied use of data science and artificial intelligence.

This position is well-suited for a hands-on practitioner who enjoys working on real operational problems and using code-first, AI-enabled approaches to identify performance risks, surface non-obvious improvement opportunities, and enable more proactive performance management.

The work primarily supports Service Level Requirements (SLRs) that govern program performance, with opportunities to extend insights and methods to broader Navy performance initiatives such as World Class Alignment Metrics (WAM).

Key Responsibilities

• Apply data science, advanced analytics, and AI techniques to large, complex operational datasets to identify performance degradation, systemic issues, and improvement opportunities
• Design and implement code-first analytical solutions and models that support automated or semi-automated discovery of performance improvement opportunities
• Use AI and data-driven methods to evaluate, prioritize, and improve the effectiveness of Plans of Action and Milestones (POAMs) tied to contractual outcomes
• Collaborate closely with performance analysts, engineers, and stakeholders to translate operational challenges into data-driven solutions
• Explore and apply appropriate AI and machine learning techniques, balancing innovation with explainability, defensibility, and stakeholder trust
• Develop reusable analytical code, methods, and patterns that strengthen the team’s overall data science and AI capabilities
• Communicate insights and recommendations clearly to both technical and non-technical audiences, including program leadership
• Support broader Navy performance initiatives by extending analytical methods beyond SLR-focused use cases when appropriate

Basic Qualifications

• Bachelor’s degree with 8+ years of experience applying data science, machine learning, or AI to real-world operational or performance problems (additional experience may be considered in lieu of degree)
• Strong problem-framing skills and ability to operate effectively in ambiguous environments
• Proficiency in Python or similar programming languages for data analysis and modeling
• Experience working with large, messy, or heterogeneous datasets
• Ability to clearly and defensibly explain complex analytical results
• Demonstrated ability to collaborate effectively as part of a multidisciplinary team
• Must be able to obtain and maintain a Secret clearance

Preferred Qualifications

• Experience with applied machine learning, statistical modeling, or AI techniques for pattern detection, prioritization, or forecasting
• Familiarity with operational performance metrics, service-level agreements, or contract-driven environments
• Experience balancing advanced analytical methods with the ability to clearly articulate complex concepts and build stakeholder trust
• Exposure to AI enablement efforts, reusable analytics frameworks, or platform-based approaches
• Experience supporting large-scale or enterprise environments, particularly within government or defense programs

Key skills/competency

• Data Science
• Artificial Intelligence
• Machine Learning
• Performance Management
• Advanced Analytics
• Python Programming
• Operational Data Analysis
• Statistical Modeling
• Stakeholder Collaboration
• Secret Clearance