Modeling and Simulation Engineer

at  SAIC

Job ID: 2501325
Location: CHANTILLY, VA, US
Date Posted: 2025-01-31
Category: Engineering and Sciences
Subcategory: Systems Engineer
Schedule: Full-time
Shift: Day Job
Travel: Yes, 10 % of the Time
Minimum Clearance Required: TS/SCI with Poly
Clearance Level Must Be Able to Obtain: None
Potential for Remote Work: No
Description
SAIC is seeking a Modeling and Simulation Engineer to fill a critical position on SAIC’s Prime Program, Landmark AOS located in Chantilly, VA. Landmark AOS is a large SETA program that supports the NRO’s Ground Enterprise Directorate (GED), which is responsible for the acquisition of systems over the complete end-to-end life cycle.
As the Modeling and Simulation Engineer you will provide specialized engineering expertise supporting the acquisition of multi-intelligence (multi-INT) software services. SAIC’s client is tasked with leading the integration of mission focused tools to foster increased efficiency, automation, and information sharing. You will also assist and advise Government managers responsible for the complete end-to-end life cycle of the customer’s Ground Enterprise.

Job Responsibilities to include:

• Leverage and advance cutting-edge modeling and simulation tools and algorithms to tackle critical automation challenges within the intelligence cycle for the Intelligence Community (IC) and Department of Defense (DoD).
• Collaborate with government, SETA, and industry partners to envision and validate a forward-looking ground architecture that supports new space systems for the customer.
• Advance modeling and simulation tools to address automation challenges in the intelligence cycle for the IC and DoD.
• Partner with government, SETA, and industry to design and validate a future ground architecture supporting new space systems.
• Define modeling requirements from user needs and system architecture, and develop scripts to automate scenario modeling and performance analysis.
• Work collaboratively to solve complex intelligence problems across domains, applying Digital Engineering to plan critical mission capabilities.
• Support a modular, real-time global surveillance architecture, assess technologies, and provide technical guidance to resolve issues in space and ground system integration.

Qualifications

Required Education and Experience

• Bachelor’s degree in business, engineering, science, or related discipline and 5 years total experience (or an MS degree and 3 years) Relevant experience to be substituted in lieu of degree.
• Active Top Secret/SCI Clearance with Polygraph.
• Experience using one or more of the following: AFSIM, C++, Python, R, SQL, PostgreSQL, Linux, MATLAB, VBA, or STK.
• Engineering analysis (collecting, organizing, analyzing data) experience.
• Practical understanding of space and/or ground systems, hardware, software, operations, and their interdependence.
• Excellent communication skills that will allow the presentation of findings to internal and external customers.
• Good working knowledge of MS Office applications.

SAIC accepts applications on an ongoing basis and there is no deadline.
Covid Policy: SAIC does not require COVID-19 vaccinations or boosters. Customer site vaccination requirements must be followed when work is performed at a customer site

• Leverage and advance cutting-edge modeling and simulation tools and algorithms to tackle critical automation challenges within the intelligence cycle for the Intelligence Community (IC) and Department of Defense (DoD).
• Collaborate with government, SETA, and industry partners to envision and validate a forward-looking ground architecture that supports new space systems for the customer.
• Advance modeling and simulation tools to address automation challenges in the intelligence cycle for the IC and DoD.
• Partner with government, SETA, and industry to design and validate a future ground architecture supporting new space systems.
• Define modeling requirements from user needs and system architecture, and develop scripts to automate scenario modeling and performance analysis.
• Work collaboratively to solve complex intelligence problems across domains, applying Digital Engineering to plan critical mission capabilities.
• Support a modular, real-time global surveillance architecture, assess technologies, and provide technical guidance to resolve issues in space and ground system integration