RF MASINT Engineering SME

KBR•Beavercreek Township, OH

About The Position

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. KBR is seeking a self-motivated KBR is seeking a self-motivated RF MASINT Engineer ing SME with an active TS/SCI clearance to develop MASINT algorithms and employ probability theories and computational methods to large datasets. These algorithms will be used to analyze and better understand threats to DoD interests. Candidate should have expert-level proficiency in MATLAB and require minimal oversight. KBR is seeking a self-motivated RF MASINT Engineer ing SME with an active TS/SCI clearance to develop MASINT algorithms and employ probability theories and computational methods to large datasets. These algorithms will be used to analyze and better understand threats to DoD interests. Candidate should have expert-level proficiency in MATLAB and require minimal oversight. At KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team’s philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver – Together. KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.

Requirements

Strong proficiency in probability theory and statistics
Experience in the application of computational Bayesian methods, such as Markov-Chain Monte Carlo analyses (e.g., Metropolis-Hastings or Gibbs Sampling) and Variational Inference
Understanding of numerical optimization techniques
Graduate degree in Engineering, Applied Physics, Applied Mathematics, or extensive relevant experience in a related technical field
Proficiency in MATLAB programming language
Ability to work independently and with teams
Must have an Active TS Clearance

Nice To Haves

Experience in applied stochastic estimation (e.g., Kalman and nonlinear filtering)
Basic understanding of classical mechanics and applications
Proficiency in C/C++ and Python programming languages
Proficiency in numerical mathematics techniques
Understanding of high-performance computing and parallel algorithm design
Experience with scientific data processing (including signal processing), modeling and simulation, and R&D algorithm development