Lead Data Scientist

The Leidos Digital Modernization Sector is seeking a highly motivated Lead Data Scientist; this position will allow for full time telework from any U.S. based location.

POSITION SUMMARY:
The Leidos Chief Data & Analytics Office (CDAO) is a new, high-growth organization at the center of the company's technology strategy. Our Operational AI (Ops.AI) division is seeking an experienced and innovative Lead Data Scientist to drive the delivery of high-impact data science solutions. This role is essential for translating complex business challenges into data-driven insights that improve mission-critical outcomes. This is an exciting opportunity to leverage your experience to solve complex problems and optimize decision-making in dynamic environments. 

PRIMARY RESPONSIBILITIES:
The Lead Data Scientist will guide a team of data scientists and analysts in the development and deployment of advanced analytical models and AI solutions. This individual will act as a technical leader and a key bridge between our data science team and business stakeholders, ensuring that our projects are technically sound, strategically aligned, and deliver measurable value. This position is key to leveraging data science to solve complex problems and accelerate innovation across Leidos. 

• Project Leadership: Lead the end-to-end execution of data science projects, from problem formulation and data exploration to model development, validation, and deployment. 
• Technical Mentorship: Provide technical mentorship and guidance to data scientists on advanced analytics, machine learning techniques, and best practices. 
• Stakeholder Collaboration: Collaborate with stakeholders to understand business needs, define project scope, and translate requirements into data science tasks. 
• Advanced Analytics Application: Drive the application of advanced techniques, including prescriptive analytics, scenario modeling, and data-to-insight transformation. 
• Quality & Rigor: Ensure the quality, rigor, and scalability of data science solutions, adhering to trusted and responsible AI principles. 
• Insight Communication: Communicate complex analytical findings and recommendations clearly to both technical and non-technical audiences to drive decision-making. 
• Innovation: Stay abreast of the latest advancements in data science and machine learning, and champion their adoption within the team. 

BASIC QUALIFICATIONS:

• Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field with 12+ years of applicable experience; additional years of experience may be substituted in lieu of a degree.
• Proven experience leading data science projects from conception to production. 
• Strong proficiency in programming languages such as Python or R and experience with common data science libraries (e.g., scikit-learn, pandas, TensorFlow, PyTorch). 
• Demonstrated expertise in machine learning, statistical modeling, and data analysis. 
• This position offers flexibility for remote or hybrid work arrangements. 
• Must be a U.S. Citizen and able to obtain and maintain a security clearance. 

PREFERRED QUALIFICATIONS:

• Experience in the national security, health, or engineering domains. 
• Experience with Generative AI, including LLMs and RAG architectures. 
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud-based data science platforms. 
• Strong project management and leadership skills. 
• A portfolio of completed data science projects or contributions to open-source projects. 

Come break things (in a good way). Then build them smarter.

We're the tech company everyone calls when things get weird. We don’t wear capes (they’re a safety hazard), but we do solve high-stakes problems with code, caffeine, and a healthy disregard for “how it’s always been done.”

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.