AFSIM Analyst
Johns Hopkins APL · Laurel, MD · Modeling/Simulation
About this role
Johns Hopkins APL is hiring a mid-level Data Analyst based in Laurel, MD. The posting calls out experience with Python, Data Structures and roughly 2+ years of relevant work. Listed education preference: a bachelor's degree or equivalent.
- Role
- Data Analyst
- Function
- data engineering
- Level
- mid
- Track
- Individual contributor
- Location
- Laurel, MD
- Experience
- 2+ years
- Education
- Bachelor's degree
- Department
- Modeling/Simulation
- Posted
- Apr 10, 2026
More roles at Johns Hopkins APL
Job description
from Johns Hopkins APL careersAre you searching for an opportunity to apply your modeling and simulation analysis background in an engaging, collegiate environment?
Are you passionate about analyzing complex problems with state of the art software and computing capabilities?
If so, then the Strike Analysis Group at the Johns Hopkins Applied Physics Lab is looking for you!
Our dedicated team of engineers, physicists, mathematicians, and computer scientists are engaged in an extensive portfolio of projects with the U.S. military. Our analysts support the acquisition, maintenance, and assessment of various aircraft and weapon assets.
We want you to join our team, and provide your background in modeling and simulation analysis to expand our capabilities and help us stay on the cutting edge of the field!
Our work is sophisticated, engaging, and frequently has significant impact to Department of Defense programs. We pride ourselves on our intellectual integrity, and our ability to deliver outstanding, unbiased analysis products. Our team emphasizes personal improvement and growth over short-lived success.
If this sounds like an environment that would help you foster and grow your interest in our domain, consider us as part of your future.
As an AFSIM Analyst…
- Your primary responsibilities will be developing models and performing analysis on sensor, tracker, communication, and weapon systems for mission-level simulations using AFSIM, with the goal of discovering useful information, informing conclusions, and supporting decision-making.