Modeling and Simulation Engineer - Data Analytics (Engineer or Principal Engineer Level

RELOCATION ASSISTANCE:
Relocation assistance may be available
CLEARANCE REQUIRED FOR START:
Yes
CLEARANCE TYPE:
Secret
TRAVEL:
Yes, 10% of the Time

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 Aeronautics Systems has an opening for a Modeling and Simulation Engineer - Data Analytics (Engineer or Principal Engineer level) to join our team of qualified, diverse individuals within our Systems Engineering organization. This role is located in San Diego, CA.

In this role, you will be responsible for supporting a data analysis effort within the Sustainment Systems Engineering team on the Triton Enterprise. You will be expected to maintain, develop, and routinely run a set of data analysis tools to help make data-driven decision making. Additionally, you will assist with network updates and maintenance of the virtual machines that host the database.

This position will work a 9/80 schedule, with every other Friday off.

• Data Architecture & Modeling – Design scalable data mining pipelines, establish protocols for data ingestion, cleaning, transformation, and storage. Evolve models to capture long term trends and support real time analytics.
• Statistical Insight – Perform exploratory data analysis, hypothesis testing, and advanced statistical modeling to identify key drivers and associations within heterogeneous data sources.
• Visualization & Reporting – Create interactive dashboards and reports using modern BI and visualization tools (e.g., MATLAB, Tableau, Power BI, Plotly) to communicate insights to technical and non technical stakeholders.
• Cross Functional Collaboration – Partner with engineering, operations, and business units to define problem statements, translate requirements into analytical solutions, and integrate findings into product roadmaps.
• Innovation & Knowledge Leadership – Stay abreast of cutting edge data science methodologies (e.g., deep learning, reinforcement learning) and evaluate their relevance to defense contexts. Mentor teams and promote a culture of data driven decision making.
• Governance & Quality – Establish data governance standards, data quality metrics, and reproducibility practices across the analytics lifecycle.

This role can be filled at an Engineer or Principal Engineer level based on the qualifications below.

At an Engineer Level:

• Must have a Bachelors of Science degree in a STEM field and at least 2 years of relevant military / professional experience, OR a Master's Degree in a STEM field and at least some of relevant military / professional / academic experience

• Must have a Bachelors of Science degree in a STEM field and at least 5 years of relevant military / professional experience, OR a Master's Degree in a STEM field and at least 3 years of relevant military / professional experience, OR a PhD and at least 1 year of relevant military / professional / academic experience

• Must have an active US Government Secret or higher clearance (with a background investigation completed within the last 6 years or currently enrolled into Continuous Evaluation).
• Must have the ability to obtain and maintain Special Access Program (SAP) clearance within a reasonable amount of time as determined by business needs.
• Must have experience in ingesting, processing, storing, analyzing and visualizing large data sets

• Demonstrated…