Principal / Senior Principal Engineer - Modeling Simulation & Analysis

Northrop Grumman•Los Angeles, CA

2d•$114,000 - $213,400•Onsite

About The Position

At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. Northrop Grumman Mission Systems is a trusted provider of mission enabling solutions for global security. Our Engineering & Sciences (E&S) organization pushes the boundaries of innovation, redefines engineering capabilities and drives advances in various sciences. Our team is chartered with providing the skills and innovative technologies to develop, design, produce and sustain optimized product lines across the sector while providing a decisive advantage to the warfighter. Come be a part of our mission! The Engineering & Sciences organization at Northrop Grumman Mission Systems (NGMS) is seeking a Principal or Senior Principal Modeling, Simulation & Analysis (MS&A) Engineer to join our team based in Woodland Hills, CA. The ideal candidate will have a strong background in physics-based modeling, simulation and data analysis, with extensive experience supporting inertial navigation products through design, verification, and performance characterization. This role requires the ability to develop and maintain high fidelity models, analyze complex multi domain data sets, and collaborate across disciplines to ensure robust system performance from concept through production.

Requirements

Bachelor’s degree in a STEM discipline plus 5 years of relevant experience; Master’s degree in a STEM discipline plus 3 years of relevant experience; PhD in a STEM discipline plus 1 year of relevant experience (for Principal MS&A Engineer).
Bachelor’s degree in a STEM discipline plus 8 years of relevant experience; Master’s degree in a STEM discipline plus 6 years of relevant experience; PhD in a STEM discipline plus 4 years of relevant experience (for Senior Principal MS&A Engineer).
Demonstrated experience in modeling, simulation, and analysis for complex systems.
Proficiency with modeling and analysis tools such as MATLAB/Simulink and Python (or comparable environments).
Experience processing and analyzing sensor or navigation data sets (e.g., IMU logs, flight test data, lab data).
Strong analytical and problem-solving skills; able to interpret complex data and generate actionable insights for design decisions and risk reduction.
Excellent written and verbal communication skills, capable of clearly presenting technical findings to both technical and non-technical audiences.
Collaborative team player who actively contributes to cross functional projects.
Meticulous attention to detail with a commitment to high quality, reliable work.
Agile and adaptable, thriving in fast changing, fast paced environments.
U.S. Citizenship required.
A current/active U.S. Government Secret clearance is required.
Availability to work onsite full-time in Woodland Hills, California.

Nice To Haves

Master’s degree or PhD in a STEM field, particularly in Aerospace Engineering, Electrical Engineering, Physics, Applied Mathematics, or related technical management.
Experience with inertial navigation systems (INS), IMU modeling, navigation algorithms, or closely related estimation or control systems.
Experience with Guidance, Navigation & Control (GNC), Kalman filtering, state estimation, or sensor fusion algorithms.
Experience integrating, validating, or troubleshooting software and simulation models within hardware environments (HIL, SIL, laboratory integration, or equivalent).
Experience with C/C++ or Python to support algorithm development or system integration.
Proven track record supporting program milestones such as SRR, SFR, PDR, and CDR, with specific contributions from modeling and analysis.

Responsibilities

Develop and maintain physics-based models and simulations of inertial navigation systems (INS), including sensors (e.g., gyros, accelerometers), error sources, and environmental effects.
Perform Monte Carlo analyses, sensitivity studies, and trade off analyses to assess system performance, robustness, and margins against requirements.
Analyze lab, flight, and field test data to validate models, quantify performance, and identify discrepancies between predicted and observed behavior.
Support requirements decomposition by providing model-based performance predictions, error budgets, and allocation rationale for key inertial navigation metrics.
Generate and maintain simulation frameworks and toolchains (e.g., MATLAB/Simulink, Python, C/C++ models) that can be reused across programs and product lines.
Collaborate closely with systems, hardware, and software engineering teams to integrate models into hardware in the loop (HIL) and software in the loop (SIL) environments, enabling early verification of navigation algorithms and interfaces.
Contribute to test planning by defining model informed test cases, corner conditions, and stress scenarios to verify navigation performance and robustness.
Analyze test and qualification results, perform root cause investigations on anomalies, and provide data driven recommendations for design updates or calibration strategies.
Prepare technical documentation and artifacts including modeling assumptions, validation reports, analysis briefs, and executive level presentations summarizing navigation performance, risks, and mitigation options.
Provide technical guidance and mentorship to junior engineers in modeling, simulation, and data analysis methods; promote best practices and knowledge sharing across disciplines.
Drive continuous improvement in MS&A processes, tools, and standards for inertial navigation products, including model re use, configuration management, and lessons learned documentation.