Data Scientist

Battelle•Chantilly, VA

13d•Hybrid

About The Position

Battelle delivers when others can’t. We conduct research and development, manage national laboratories, design and manufacture products and deliver critical services for our clients—whether they are a multi-national corporation, a small start-up or a government agency. We recognize and appreciate the value and contributions of individuals from a wide range of backgrounds and experiences and welcome all qualified individuals to apply. Job Summary At Battelle, experience matters, especially when addressing the complexities of chemical, biological, radiological, nuclear, and explosives (CBRNE) challenges. For over 70 years, government agencies and industries have trusted us to provide solutions for some of their most critical CBRNE issues. Battelle is home to advanced facilities and leading industry experts who deliver end-to-end solutions—from threat awareness to complex systems integration—ensuring the nation is prepared to respond to both current and emerging threats. Our commitment to safety and innovation makes us a leader in the field, dedicated to protecting national security and public safety. We are currently seeking a Data Scientist. This position is a full-time opportunity located in Chantilly, VA. Battelle's Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Business Line is seeking a skilled and curious Data Scientist to provide direct support at a client facility. The selected candidate will apply expertise in machine learning, data engineering, and multi-source data analysis to advance critical client missions across science and technology domains. This role requires strong technical proficiency in data science tools and methodologies, a passion for solving mission-critical challenges, and the ability to operate effectively in a fast-paced, agile environment both independently and as part of a multidisciplinary team.

Requirements

Bachelor's degree with 8+ years of relevant experience; Master's degree with 5+ years of relevant experience; PhD in a relevant field with 3+ years of experience; or an equivalent combination of education and experience
Experience using tools for collecting, assembling, interpreting, translating, and analyzing multi-source data — including science and technology information, network data, open-source data, and databases — and synthesizing findings into actionable intelligence
Experience applying machine learning, statistics, and/or data mining techniques to derive insights from complex datasets
Experience with automation of data pipelining processes, data transformation, databases, and/or repositories
Experience assessing and reporting on technologies and scientific topics, including technology readiness levels (TRL) and critical technology elements (CTE)
Experience with diverse media and advanced science and technology data
Experience in national security, defense, and/or intelligence community programs
Enthusiasm for learning new technical subject areas and curiosity about science and technology missions
Must be a U.S. citizen with an active TS/SCI clearance with polygraph

Responsibilities

Design and implement machine learning, statistical, and data engineering techniques to advance client missions across science and technology domains
Apply technical proficiency in data collection and analysis tools to improve existing techniques and devise new approaches to solve mission-critical data science challenges
Independently propose, develop, and execute creative solutions to unique data science problems, including identifying new data sources and data exploitation techniques
Collect, organize, and analyze technical information from multiple sources to drive client missions and quick-turn tasks in fast-paced environments
Provide thorough, complete work products that require minimal revision or editing
Proactively manage expectations, communicate progress, and meet deadlines in a fast-moving, agile environment
Collaborate effectively across multidisciplinary teams, including co-located and geographically distributed team members, while leading tasks on time and within budget