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Modeling Simulation Analyst Jobs in Michigan (NOW HIRING)

This role focuses on building and analyzing discrete event simulation models to guide factory and line design decisions before RFQ and detailed design. You will work closely with Body, GA, Paint ...

Troubleshoot and debug throughput simulation models. * Travel to plant sites, as necessary ... Strong analytical skills to address unusual or complex problems. No Sponsorship is available at ...

... a model that will accurately identify bottleneck areas and guide the launch and plants teams to the right areas for throughput improvements. The Simulation Engineer will analyze system and provide ...

Troubleshoot and debug throughput simulation models. * Travel to plant sites, as necessary ... Strong analytical skills to address unusual or complex problems. No Sponsorship is available at ...

Build discrete event simulation models (FlexSim preferred) for manufacturing and material flow use ... analysis. * Solid understanding of manufacturing KPIs (JPH, JPS, OEE/TEE, MTBF/MTTR, WIP, buffer ...

Troubleshoot and debug throughput simulation models. * Travel to plant sites, as necessary ... Strong analytical skills to address unusual or complex problems. No Sponsorship is available at ...

Build discrete event simulation models (FlexSim preferred) for manufacturing and material flow use ... analysis. * Solid understanding of manufacturing KPIs (JPH, JPS, OEE/TEE, MTBF/MTTR, WIP, buffer ...

Mentor junior engineers through technical guidance in modeling, simulation, and powertrain analysis. * Develop and maintain powertrain analysis tools, models, and best practices. * Contribute to ...

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Modeling Simulation Analyst information

See Michigan salary details

$17

$40

$66

How much do modeling simulation analyst jobs pay per hour?

As of May 28, 2026, the average hourly pay for modeling simulation analyst in Michigan is $40.41, according to ZipRecruiter salary data. Most workers in this role earn between $27.93 and $50.67 per hour, depending on experience, location, and employer.

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

To thrive as a Modeling Simulation Analyst, you need a strong background in mathematics, statistics, and computer science, often supported by a relevant degree such as in engineering or applied mathematics. Proficiency in simulation software (e.g., MATLAB, Simulink, Arena), programming languages (such as Python or C++), and familiarity with data analysis tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills set top candidates apart in this role. These abilities are vital for developing accurate models, interpreting complex data, and clearly presenting findings to support strategic decision-making.

How does a Modeling Simulation Analyst typically collaborate with cross-functional teams during a project?

Modeling Simulation Analysts frequently work alongside engineers, data scientists, and project managers to develop and refine simulation models. Collaboration often involves gathering system requirements, validating model assumptions with subject matter experts, and presenting simulation results to stakeholders. Clear communication is essential, as analysts must translate complex simulation data into actionable insights for decision-makers. Regular team meetings and iterative feedback are common to ensure the models accurately reflect real-world scenarios and project goals.

What are Modeling Simulation Analysts?

Modeling Simulation Analysts are professionals who use mathematical models, simulations, and analytical techniques to study complex systems and predict their behavior. They help organizations make informed decisions by evaluating scenarios, testing hypotheses, and optimizing processes through virtual models. These analysts work in various industries, including defense, healthcare, manufacturing, and transportation, to improve efficiency, reduce costs, and support planning and strategy. Their work often involves collaboration with engineers, scientists, and decision-makers to interpret simulation results and implement solutions.

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

AspectModeling Simulation AnalystData Analyst
Required CredentialsBachelor's or master's in engineering, computer science, or related fields; proficiency in simulation softwareBachelor's in statistics, mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentEngineering labs, simulation centers, or technical departmentsOffice settings, data centers, or business environments
Employer & Industry UsageManufacturing, aerospace, defense, or engineering firmsFinance, healthcare, marketing, or business sectors
Common Search & ComparisonYesYes

The Modeling Simulation Analyst focuses on creating and analyzing simulations to predict system behaviors, often requiring engineering or technical expertise. In contrast, Data Analysts interpret data sets to inform business decisions, typically using statistical tools. While both roles involve data handling, the Modeling Simulation Analyst emphasizes modeling complex systems, whereas Data Analysts focus on data interpretation for strategic insights.

What job categories do people searching Modeling Simulation Analyst jobs in Michigan look for? The top searched job categories for Modeling Simulation Analyst jobs in Michigan are:
What cities in Michigan are hiring for Modeling Simulation Analyst jobs? Cities in Michigan with the most Modeling Simulation Analyst job openings:
Simulation Test Engineer

Other

Posted 14 days ago


Job description

Job Description:

  • We are seeking a Simulation & Scenario Engineer to support Level 3 and Level 4 automated driving development through scenario-based validation and virtual testing.
  • This role focuses on designing, building, and executing complex driving scenarios from scratch in simulation environments, with a strong emphasis on safety, robustness, and edge-case handling.
  • The ideal candidate has hands-on experience in ADAS or autonomous driving simulation and understands system behavior in complex, safety-critical environments.

Education:

  • BS or MS Degree in Computer Science, Robotics, Automotive Engineering, Systems Engineering, or equivalent.

Experience Requirements:

  • 3+ years (Level 3 focus) or 5+ years (Level 4 focus) in ADAS or autonomous driving environments.
  • Proven experience creating simulation scenarios from scratch (not limited to log replay).
  • Strong exposure to scenario-based validation and system behavior evaluation.
  • Experience working within defined ODDs (Operational Design Domains).
  • Safety-related experience (simulation validation, safety analysis, system behavior modeling).
  • Strong Python development experience in Linux environment (CLI-based workflows).
  • Hands-on experience with simulation tools such as:
    • Applied Intuition
    • MATLAB / Simulink
    • CARLA
    • LGSVL Simulator
    • Or equivalent platforms

Key Responsibilities:

  • Design and build autonomous driving simulation scenarios from scratch.
  • Recreate real-world traffic situations across different environments (urban, semi-urban, highway).
  • Configure and control dynamic agents (vehicles, pedestrians, cyclists, traffic actors) programmatically.
  • Develop, modify, and maintain Python scripts to generate and execute simulation pipelines.
  • Execute simulations via command-line interfaces and manage configurations.
  • Assess system behavior with strong focus on:
    • Safety
    • Robustness
    • Edge-case handling
    • Fallback / takeover logic (Level 3)
    • Full autonomy behavior (Level 4)
  • Identify unrealistic, unsafe, or inconsistent behaviors and support corrective improvements.
  • Support validation, verification, and safety compliance activities (e.g., ISO 26262 awareness).
  • Collaborate cross-functionally with perception, planning, controls, and safety teams.
  • Document simulation assumptions, configurations, and validation results.

Profile:

  • Simulation Engineer - ADAS / Autonomous Driving
  • Mid to Senior Level
  • Strong analytical and systems-thinking mindset
  • Safety-oriented and detail-driven
  • Hands-on and technically proactive
  • Comfortable working in fast-paced, agile environments

Must Have:

  • Experience building simulation scenarios from scratch.
  • Strong exposure to ADAS or autonomous driving systems.
  • Solid Python scripting experience.
  • Comfortable working in Linux and command-line environments.
  • Experience configuring and controlling simulation agents programmatically.
  • Understanding of vehicle behavior in safety-critical and complex environments.
  • Ability to debug and modify simulation models and scripts.
  • Experience collaborating in cross-functional engineering teams.

Good to Have:

  • Experience in Level 3 takeover/fallback validation.
  • Experience in Level 4 urban autonomy or robotaxi programs.
  • Exposure to edge-case generation and scenario explosion methodologies.
  • Knowledge of ISO 26262 or automotive safety processes.
  • Experience with perception, planning, or sensor fusion validation.
  • Experience in large-scale simulation automation pipelines.
  • Experience working in global or multicultural teams.
  • Ability to mentor junior engineers.