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Monte Carlo Simulation Jobs (NOW HIRING)

MDAEdge

Python Developer - Oil & Gas Sector

Houston, TX · On-site

$48 - $66/hr

The role involves developing Python-based analytics workflows, building Monte Carlo simulations, and creating visualizations to communicate insights to stakeholders. Responsibilities : • Develop ...

Virgin Galactic

Sr. Engineer, Aerodynamics

Tustin, CA · On-site

$108K - $166K/yr

In this role, you will be a primary contributor to the development and maintenance of simulation tools that support trajectory analysis, handling qualities evaluation, and Monte Carlo-based ...

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Monte Carlo Simulation information

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$11K

$67.6K

$121.5K

How much do monte carlo simulation jobs pay per year?

As of Aug 17, 2026, the average yearly pay for monte carlo simulation in the United States is $67,601.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $79,500.00 per year, depending on experience, location, and employer.

What is a Monte Carlo simulation?

A Monte Carlo Simulation job typically involves using statistical techniques to model uncertainty and predict outcomes in various fields such as finance, engineering, and risk analysis. Professionals in this role develop and implement stochastic models to analyze complex systems and optimize decision-making. They often work with programming languages like Python, R, or MATLAB and apply probability theory to simulate real-world scenarios.

What are the typical daily responsibilities for someone working in Monte Carlo simulation roles?

Professionals in Monte Carlo Simulation roles typically spend their days developing, running, and analyzing computational models to assess risk, forecast outcomes, or optimize processes. Responsibilities often include collaborating with cross-functional teams to define model parameters, preparing and cleaning large datasets, coding simulation algorithms, and interpreting results to guide business or engineering decisions. You may also present findings to non-technical stakeholders and document methodologies for reproducibility. This role offers a dynamic blend of independent technical work and collaborative problem-solving, making it ideal for those who enjoy both analytical tasks and teamwork.

What are the key skills and qualifications needed to thrive in the Monte Carlo simulation position, and why are they important?

To thrive as a Monte Carlo Simulation specialist, you need strong quantitative skills, a background in mathematics, statistics, or engineering, and experience with probability-based modeling. Expertise with programming tools such as Python, MATLAB, R, or specialized simulation software, along with knowledge of data analysis and modeling techniques, is typically required. Attention to detail, analytical thinking, and effective communication are vital soft skills for interpreting results and presenting findings to stakeholders. These competencies are crucial for creating accurate models, troubleshooting complex problems, and making data-driven recommendations in various industries.

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Monte Carlo Simulation jobs near you
Infographic showing various Monte Carlo Simulation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $67,601 per year, or $32.5 per hour.

AI System Analyst (AI Monte Carlo)

Saransh Inc

Houston, TX • On-site

Contractor

Re-posted 25 days ago

Job description

Role: AI System Analyst (AI Monte Carlo)
Client address: Houston, TX (Hybrid)
Contract
 
Experience Required: 10-12 years
 
Mandatory skills:
  • AI Monte Carlo
  • Python
     
Key Responsibilities:
  • Solution Architecture: Design and implement advanced Monte Carlo simulation frameworks to solve complex probabilistic problems (e.g., risk assessment, optimization, or predictive forecasting).
  • Client Engagement: Lead discovery sessions with clients to extract and define technical requirements from high-level business goals.
  • Cross-Functional Collaboration: Serve as the primary technical liaison between functional business units and core engineering teams to ensure alignment on deliverables.
  • End-to-End Delivery: Own the full lifecycle of AI development—from algorithmic design and data modeling to deployment and performance tuning.
  • Mentorship & Leadership: Provide technical guidance to junior/mid-level developers while maintaining the self-sufficiency to handle critical individual contributor tasks in agile environments.
Technical Qualifications:
  • Core AI & Math: Expert knowledge of Monte Carlo methods (MCMC, Sequential Monte Carlo, Quasi-Monte Carlo) and their application in AI/ML environments.
  • Programming: Mastery of Python or C++ (high-performance computing experience is a major plus).
  • Infrastructure: Solid understanding of cloud-based AI deployment (AWS, Azure, or GCP) and containerization (Docker/Kubernetes).
  • Strategic Thinking: 10+ years of experience navigating the trade