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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 ...

Lancesoft

Analog Designer 3

Boxborough, MA · On-site

$60.09 - $63.43/hr

Verify circuit robustness using Monte Carlo simulation. Characterize standard cell libraries for custom PVTS. EXPERIENCE AND EDUATION: 5-7 years of relevant work experience;Experience with Schematic ...

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Monte Carlo Simulation information

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How much do monte carlo simulation jobs pay per year?

As of Jul 27, 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 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.

What is a Monte Carlo Simulation job?

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 is an example of a Monte Carlo simulation in real life?

A Monte Carlo simulation, used by professionals in fields like finance and engineering, models complex systems by running numerous random scenarios to estimate outcomes. For example, it can predict investment portfolio risks by simulating thousands of market conditions, helping analysts assess potential gains or losses. Skills in statistical analysis and familiarity with simulation software are essential for this role.

What job makes $1,000,000 a year?

In the field of Monte Carlo simulation, high-paying roles such as quantitative analysts, financial engineers, or senior risk managers in finance can earn around or above $1 million annually, especially with bonuses and profit sharing. These positions typically require advanced degrees, strong programming skills, and experience with complex modeling tools like MATLAB or Python in a high-pressure environment.

How much do software engineers make at Monte Carlo?

Software engineers at Monte Carlo typically earn salaries ranging from $100,000 to $150,000 annually, depending on experience, location, and skill set. Compensation may also include bonuses and stock options, especially for senior roles or specialized positions involving data analysis and automation tools.

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.

More about Monte Carlo Simulation jobs
What cities are hiring for Monte Carlo Simulation jobs? Cities with the most Monte Carlo Simulation job openings:
What are the most commonly searched types of Monte Carlo Simulation jobs? The most popular types of Monte Carlo Simulation jobs are:
What states have the most Monte Carlo Simulation jobs? States with the most job openings for Monte Carlo Simulation jobs include:
What job categories do people searching Monte Carlo Simulation jobs look for? The top searched job categories for Monte Carlo Simulation jobs are:
Monte Carlo Simulation jobs near you
Infographic showing various Monte Carlo Simulation job openings in the United States as of July 2026, with employment types broken down into 4% Internship, 5% As Needed, 88% Full Time, 1% Part Time, 1% Contract, and 1% Nights. Highlights an 89% Physical, 5% Hybrid, and 6% 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

Posted 5 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