Principal Data Scientist

KBR•Reston, VA

4d•$172,000 - $212,000•Onsite

About The Position

KBR is seeking a Principal Data Scientist to join a multidisciplinary team of operational military and intelligence subject matter experts, operations research analysts, modelers, and software engineers. The team conducts modeling, simulation, and analysis of emerging concepts using advanced techniques and tools. The role develops analytical prototypes, data workflows, visualizations, and decision-support capabilities that support modeling, simulation, experimentation, and assessment. The selected candidate will collaborate with analysts, stakeholders, and software developers to translate mission needs into analytical solutions, demonstrate operational value, and support transition of prototypes into software development and operational deployment. The position is on-site, has standard working hours, and requires minimal travel (0–20%). The role requires a master’s degree in a quantitative discipline and 12 years of relevant experience, proficiency in Python and scientific/data-analysis libraries, experience with analytical applications and data workflows, and a current Top Secret clearance with the ability to obtain and maintain SCI and SAP eligibility. A Ph.D. and experience in national security, MS&A tools, machine learning, containerized application deployment, or prototype-to-production transition are desired. The Virginia compensation range is $172,000 to $212,000. KBR may also provide additional compensation such as bonuses, commissions, sign-on bonuses, relocation benefits, short- or long-term incentives, or discretionary performance payments. Benefits may include a 401(k) plan with company match, medical, dental, vision, life and disability insurance, AD&D, flexible spending account, paid time off, flexible work schedule, and professional training and development.

Requirements

Master’s degree in Data Science, Operations Research, Applied Mathematics, Statistics, Computer Science, or a related quantitative discipline, with 12 years of relevant experience.
Demonstrated experience applying data science, statistical analysis, or quantitative methods to solve complex operational, technical, or business problems.
Proficiency with Python and commonly used scientific and data-analysis libraries such as Pandas, NumPy, SciPy, Scikit-learn, and Plotly, or comparable tools.
Experience developing analytical applications, dashboards, visualizations, or decision-support tools, including web-based solutions deployed in modern computing environments.
Experience developing, managing, and automating data collection, integration, transformation, and analysis workflows.
Experience working with structured and unstructured data from multiple sources.
Experience analyzing data generated through modeling and simulation environments.
Ability to communicate complex technical concepts and analytical results to diverse audiences, including senior decision-makers.
Experience working collaboratively within multidisciplinary teams of technical and non-technical personnel.
Strong written and verbal communication skills.
Current Top Secret clearance with the ability to obtain and maintain Sensitive Compartmented Information (SCI) and Special Access Program (SAP) eligibility.

Nice To Haves

Ph.D. in Data Science, Operations Research, Applied Mathematics, Statistics, Computer Science, or a related quantitative discipline.
Experience supporting Department of Defense, Combatant Command, Service, Joint, Intelligence Community, or other National Security organizations.
Familiarity with AFSIM, NGTS, STORM, EADSIM, mission engineering frameworks, or comparable MS&A tools and methodologies.
Experience developing rapid prototypes, proof-of-concept applications, or analytical demonstrations that transitioned into production environments and software implementations.
Experience developing standalone analytical applications, dashboards, or decision-support tools and transitioning analytical prototypes into operational capabilities through user engagement and collaboration with software development teams.
Experience developing standalone analytical applications, dashboards, or decision-support tools that integrate data processing, visualization, and user interaction capabilities.
Experience deploying and maintaining analytical applications in containerized environments using Docker, Rancher, Kubernetes, or similar platforms.
Familiarity with software development practices, version control systems, DevSecOps concepts, and Agile development methodologies.
Experience applying machine learning, artificial intelligence, or advanced statistical techniques to analytical and decision-support problems.
Experience mentoring, guiding, or providing technical support to less-experienced team members.
Demonstrated ability to assume increasing technical responsibility and contribute to the growth of analytical capabilities and organizational expertise.

Responsibilities

Develop analytical prototypes, dashboards, and decision-support tools supporting modeling, simulation, experimentation, and assessment activities.
Design, develop, and maintain data pipelines and workflows that integrate, transform, and analyze data from multiple sources.
Apply data science, statistical, and computational methods to analyze complex datasets, including modeling and simulation outputs.
Collaborate with analysts, subject matter experts, stakeholders, and software developers to translate mission needs into analytical solutions.
Build proof-of-concept capabilities that demonstrate operational value and support transition to software development and operational deployment.
Develop visualizations, dashboards, and reporting products that communicate analytical results to technical and non-technical audiences.
Evaluate and apply emerging technologies, including AI-enabled development tools, to improve analytical workflows and prototype development.
Present findings, recommendations, and technical approaches to sponsors and stakeholders.
Document methodologies, assumptions, and prototype capabilities to support knowledge transfer and repeatability.
Contribute to the continuous improvement of MS&A processes, tools, and analytical practices.

Benefits

401(k) plan with company match
Medical insurance
Dental insurance
Vision insurance
Life insurance
AD&D coverage
Flexible spending account
Disability insurance
Paid time off
Flexible work schedule
Professional training and development
Additional compensation may include sign-on bonus, relocation benefits, short-term incentives, long-term incentives, or discretionary payments for exceptional performance.