Data Scientist - Senior

Leidos
Fort Meade, MDPosted 9 March 2026

Job Description

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 sustainable. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. Our Mission, Vision, and Values guide the way we do business. If this sounds like the kind of environment where you can thrive, keep reading! The Opportunity Are you ready to shape the future of global security? The Leidos Intelligence Sector is seeking a highly motivated Data Scientist for USCYBERCOM J2 to conduct advanced data analytics, data engineering, data mining, exploratory and predictive analysis, and statistical analysis in support of informed analytic and operational decision-making. The Data Scientist will employ scientific techniques to correlate complex multi-source data, producing graphical, written, visual, and verbal narrative products. This role requires proactively retrieving, integrating, and analyzing data from a wide variety of internal and external sources, and building artificial intelligence (AI) and machine learning (ML) tools that automate processes and enable enhanced mission effectiveness. Join a team where your "greatest work" isn't just a slogan—it’s our daily standard. Contract Status: Proposal Phase/Contingent Upon Award. Security Clearance: Active DoD TS/SCI with Polygraph required. We are not able to sponsor the clearance requirement. What you'll be doing: Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis to uncover insights and enable data-driven decisions. Use scientific methods to transform raw data into actionable narrative products, including graphical, visual, written, and verbal reports tailored for stakeholders. Retrieve, manage, and merge data from disparate sources to build comprehensive and accurate datasets for analysis. Design, develop, and implement ML-based tools and processes, such as recommendation engines, automated lead scoring systems, and predictive analytics solutions. Perform statistical analysis and data mining techniques to identify patterns, trends, correlations, and build high-quality prediction systems supporting mission-critical objectives. Present analytic findings using advanced data visualization tools and graphical applications to intuitively communicate complex information. Document Operating Instructions (OIs) for command-wide programs and initiatives as assigned by the Government. Collaborate with analysts, engineers, and operations personnel to align analytic models and tools with mission requirements and evolving data needs. Stay abreast of advancements in data science, ML/AI technologies, and analytic tools to continuously improve analytic capabilities and workflows. Needed Experience, Skills, and Education: Minimum 12 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years. Master’s degree in an area related to the labor category from a college or university accredited by an agency recognized by the U.S. Department of Education; or have Bachelor’s degree related to the labor category from a college or university accredited by an agency recognized by the U.S. Department of Education and an additional 5 years of related senior experience, for a total of 17 years, as a substitute to the Master’s degree. Additional years of experience may be considered in lieu of degree. Proficiency in data visualization and graphical applications, such as Microsoft Office (Power BI), Tableau, or equivalent tools. Experience with data science programming languages, such as R and Python. Advanced skills in managing, merging, and analyzing disparate data sources, preferably through R, Python, or SQL. Demonstrated expertise in applying statistical analysis, data m ... (truncated, view full listing at source)
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