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Simulation Modeling Python Jobs (NOW HIRING)

Kaygen Inc

Simulation Engineer

Liberty, NC · On-site

Proven expertise using Siemens Plant Simulation software for building and applying DES models. * Knowledge of programming or scripting languages (e.g., Python, SQL) to automate data processing or ...

CTC

Senior Simulation Engineer

Liberty, NC · On-site

Proven expertise using Siemens Plant Simulation software for building and applying DES models. * Knowledge of programming or scripting languages (e.g., Python, SQL) to automate data processing or ...

SAIC

Modeling and Simulation Engineer

Chantilly, VA

As the Modeling and Simulation Engine, you will provide technical expertise on a variety of ... Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis ...

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How much do simulation modeling python jobs pay per year?

As of Jun 6, 2026, the average yearly pay for simulation modeling python in the United States is $139,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $164,500.00 per year, depending on experience, location, and employer.

What is simulation modeling in Python?

Simulation modeling in Python involves using the Python programming language to create models that mimic real-world systems or processes. These models allow users to experiment with different variables and scenarios to predict outcomes, optimize performance, and understand complex systems without real-world risks or costs. Python is popular for simulation modeling due to its readability, extensive libraries like SimPy and NumPy, and strong community support. Simulation modeling is used in fields such as engineering, logistics, healthcare, and finance to analyze systems and make data-driven decisions.

What are some common challenges faced when developing simulation models in Python, and how can they be addressed in a collaborative team environment?

Simulation modeling in Python often involves handling complex systems, large datasets, and ensuring model accuracy, which can present challenges such as debugging intricate code, validating results, and optimizing performance. Collaborating in a team requires effective communication and version control practices to manage code changes and integrate different model components. Using tools like Git for version control, establishing clear documentation standards, and conducting regular code reviews can help address these challenges, streamline development, and promote knowledge sharing among team members.

What are the key skills and qualifications needed to thrive as a Simulation Modeling Python Specialist, and why are they important?

To excel in Simulation Modeling with Python, you need a solid background in mathematics, statistics, and programming, typically supported by a degree in engineering, computer science, or a related field. Expertise in Python libraries such as NumPy, SciPy, SimPy, and experience with data visualization tools are commonly required, along with familiarity in simulation frameworks and possibly certifications in data science or analytics. Strong analytical thinking, problem-solving abilities, and effective communication skills help translate complex simulation outcomes into actionable insights. These competencies enable professionals to design accurate models, interpret results effectively, and support data-driven decision-making across various industries.

What is the difference between Simulation Modeling Python vs Data Analyst?

AspectSimulation Modeling PythonData Analyst
Required SkillsPython programming, simulation techniques, mathematical modelingData analysis, Excel, SQL, statistical tools
Work EnvironmentResearch labs, engineering firms, tech companiesBusiness, finance, marketing departments
CertificationsPython certifications, modeling coursesData analysis certifications, SQL certifications
Industry UsageSimulation of systems, process optimizationData reporting, trend analysis, decision support

Simulation Modeling Python focuses on creating models and simulations using Python to analyze complex systems, often in engineering or research contexts. Data Analysts interpret data to inform business decisions, utilizing statistical tools and data visualization. While both roles require analytical skills, Simulation Modeling Python emphasizes technical modeling expertise, whereas Data Analysts focus on data interpretation and reporting.

Infographic showing various Simulation Modeling Python job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $139,971 per year, or $67.3 per hour.
Senior Engineer, XBAT Simulation Modeling (R4546) (TX/SD/BOS)

Senior Engineer, XBAT Simulation Modeling (R4546) (TX/SD/BOS)

Shield AI

San Diego, CA • On-site

Full-time

Posted 28 days ago

Job description

JOB DESCRIPTION:
The Aircraft Simulation team turns frontier autonomy into mission-ready aircraft. We own the commit-to-flight pipeline—deterministic aircraft and mission simulation, HITL/SITL integration, CI/CD, and tooling for automated flight qualification testing. Our goal is simple: make AI fly—safely, reliably, and fast.
As a Senior Modeling & Simulation Engineer, you will be dedicated to Shield AI’s next-generation aircraft program, contributing to our modeling and simulation tooling pipeline. You’ll design, build, and scale novel aircraft subsystem models, develop infrastructure that enables automated testing for our XBAT product line, and perform verification and validation of simulation pipelines. You will also conduct system performance analysis to evaluate expected and actual flight and mission performance using simulation tools and publish results for consumption by customers.
What You'll Do
  • Develop models and infrastructure for the integrated simulation pipeline in C++
  • Design deterministic, high-performance simulation tools capable of faster-than-real-time execution for development, testing, and release. 
  • Implement test scenarios and write unit, system, and regression tests. 
  • Collaborate across autonomy, embedded, GNC, and test engineering to ensure the simulation mirrors real aircraft behavior and mission scenarios. 
  • Contribute to platform-agnostic simulation tooling to accelerate future development efforts 
  • Perform verification and validation (V&V) analysis activities on model tools. 
  • Conduct system performance analysis and generate reports and visualizations. 
  • Utilize best practices in C++, simulation architecture, and performance engineering.
Required Qualifications
  • BS or MS in Computer Science, Aerospace, Robotics, or related field. 
  • 5+ years of experience in software development, with emphasis on modern C++ (C++17 or later) and performance optimization. 
  • Strong understanding of rigid-body dynamics, kinematics, and basic flight and sensor mechanics. 
  • Proven experience developing or integrating simulation systems for robotics, aerospace, or autonomous systems. 
  • Ability to debug complex build and runtime environments (CMake, CPM, package management, logging, & profiling tools). 
  • Experience with software testing tools (GTest, etc.) 
  • Experience with model V&V. 
  • Strong collaboration and communication skills across software, hardware, and systems disciplines.
Preferred Qualifications
  • Grasp of real-time and deterministic software design, including multi-threading, synchronization, and memory management. 
  • Experience with DevOps-integrated simulation workflows, including CI/CD and automated hardware testing environments.
  • Working knowledge of Python for data analysis, test automation, or simulation orchestration. 
  • Familiarity with aircraft and flight physics modeling. 
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