Data Scientist
Data Scientist Belong. Connect. Grow. with KBR! KBR's National Security Solutions team provides high-end engineering and advanced technology solutions to our customers in the intelligence and national security communities. In this position, your work will have a profound impact on the country's most critical role - protecting our national security. Why Join Us?
- Innovative Projects: KBR's work is at the forefront of engineering, logistics, operations, science, program management, mission IT and cybersecurity solutions.
- Collaborative Environment: Be part of a dynamic team that thrives on collaboration and innovation, fostering a supportive and intellectually stimulating workplace.
- Impactful Work: Your contributions will be pivotal in designing and optimizing defense systems that ensure national security and shape the future of space defense.
- Design, develop, and maintain analytic solutions using ECL and HPCC Systems to process and analyze large-scale datasets.
- Develop, validate, and apply methodologies that support complex analytic requirements within clustered computing environments.
- Create and maintain data models that support enterprise and mission-focused analytics.
- Use programming languages such as Python, R, Pig, Java, C, and SQL to perform large-scale parallel processing and data analysis.
- Design and optimize scalable data ingestion, transformation, and enrichment workflows across distributed computing platforms.
- Collaborate with engineers, analysts, and mission stakeholders to translate analytical requirements into technical solutions.
- Validate data quality, analytical methods, and outputs to ensure accurate and reliable results.
- Location: On-site
- Travel Requirements: Minimal
- Working Hours: Standard
- Active TS/SCI with a Polygraph
- Minimum of 10 years experience
- Minimum three (3) years of experience using ECL within the HPCC Systems environment.
- Demonstrated experience with data modeling and large-scale data analytics.
- Experience using Python, R, Pig, Java, C, or SQL to perform large-scale parallel processing of data.
- Experience developing, validating, and applying methodologies to support analytic requirements in clustered computing environments.
- Experience working with distributed computing, high-volume datasets, and scalable data processing architectures.
- Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related technical field.
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