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.
- Conducts scientific Research and Development towards the tasking, collection, processing, and dissemination of data.
- Collects substantial amounts of data using analytical, statistical, and programmable skills.
- Analyze data sets to discover actionable patterns and trends for business use.
- Uses scientific methods, processes, algorithms, and systems to extract insights from structured and unstructured data.
- Applies mathematical, problem-solving, and coding skills to manage big data, extracting valuable insights.
- Assess other's R&D proposals for feasibility and progress towards mission goals.
- Solve difficult, non-routine problems by applying advanced analytical methodologies and improving analytic methodologies.
- Developing custom searches.
- Communicating and coordinating with internal and external partners as needed.
- Other duties as assigned.
- Active TS/SCI with Polygraph.
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
- Minimum of 10 years of experience in data science or related roles.
- Expert-level proficiency in Python or R.
- Strong experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch).
- Deep understanding of statistical modeling, experimental design, and advanced analytics.
- Proficiency in SQL and working with large-scale datasets.
- Experience building and deploying production-ready models.
- Strong software engineering practices (version control, testing, modular coding).
- Excellent communication and storytelling skills with data.
- Experience with big data technologies (Spark, Hadoop).
- Experience working with cloud platforms (AWS, Azure, or Google Cloud).
- Knowledge of MLOps tools and practices (CI/CD, model monitoring, containerization).
- Experience with deep learning, NLP, recommender systems, or time-series forecasting.
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