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Full Time Monte Carlo Simulation Jobs (NOW HIRING)

CMCOM LLC

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Senior Construction Management Project Risk Management Professional

Manhattan, NY · On-site

$70 - $120/hr

New York / New Jersey Port District | Hybrid Potential Employment Type: Full-Time W-2 Employee Pay ... Perform quantitative risk modeling, including Monte Carlo simulation, cost-risk analysis, schedule ...

CMCOM LLC

Be Seen First

Senior Construction Management Project Risk Management Professional

Manhattan, NY · On-site

$70 - $120/hr

New York / New Jersey Port District | Hybrid Potential Employment Type: Full-Time W-2 Employee Pay ... Perform quantitative risk modeling, including Monte Carlo simulation, cost-risk analysis, schedule ...

Peraton

Risk Analysis Engineer

Annapolis Junction, MD · On-site

$86K - $138K/yr

Implement Monte Carlo simulation engines for schedule risk analysis (SRA) and cost risk analysis * Design risk scoring models that combine traditional likelihood/impact matrices with NLP-detected ...

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Full Time Monte Carlo Simulation information

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How much do full time monte carlo simulation jobs pay per year?

As of Jun 9, 2026, the average yearly pay for full time 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 and what does a Full Time Monte Carlo Simulation job involve?

A Monte Carlo Simulation is a computational technique that uses random sampling to estimate complex mathematical or physical systems, often used to model uncertainty and forecast outcomes in fields like finance, engineering, and scientific research. A Full Time Monte Carlo Simulation job typically involves developing, implementing, and analyzing simulation models to provide insights or solve problems for businesses or research projects. Professionals in this role often use programming languages such as Python, R, or MATLAB, and require strong analytical, mathematical, and statistical skills. They may work in industries such as finance, insurance, energy, or manufacturing, helping organizations make informed decisions based on probabilistic modeling.

What are some common challenges faced by professionals working full time with Monte Carlo simulations, and how can they be addressed?

Professionals working full time with Monte Carlo simulations often encounter challenges such as managing computational complexity, ensuring accurate input data, and interpreting probabilistic results for stakeholders. Efficiently optimizing code and leveraging parallel computing can help address performance issues, while thorough validation and sensitivity analysis improve model reliability. Collaborating closely with subject matter experts ensures that simulation inputs and assumptions are realistic, ultimately leading to more actionable insights.

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

To excel as a Monte Carlo Simulation Specialist, you need strong quantitative analysis skills, a background in mathematics, statistics, or engineering, and typically a relevant degree. Proficiency in programming languages like Python, R, or MATLAB, as well as experience with simulation software and statistical packages, is crucial. Attention to detail, problem-solving abilities, and effective communication help explain complex results to stakeholders. These skills ensure accurate modeling, reliable risk assessments, and actionable insights for data-driven decision-making.

What is the difference between Full Time Monte Carlo Simulation vs Quantitative Analyst?

AspectFull Time Monte Carlo SimulationQuantitative Analyst
CredentialsDegree in Mathematics, Statistics, or FinanceDegree in Finance, Economics, or Mathematics
Work EnvironmentFinancial institutions, risk management teamsInvestment banks, hedge funds, asset management firms
Industry UsageRisk modeling, option pricing, simulationsMarket analysis, trading strategies, risk assessment

Full Time Monte Carlo Simulation specialists focus on developing and running complex simulations to assess financial risks and pricing models. Quantitative Analysts, while often utilizing Monte Carlo methods, have broader roles including data analysis, modeling, and strategy development. Both roles require strong quantitative skills and work in similar financial environments, but their primary responsibilities differ in scope and application.

More about Full Time Monte Carlo Simulation jobs
What cities are hiring for Full Time Monte Carlo Simulation jobs? Cities with the most Full Time 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 job categories do people searching Full Time Monte Carlo Simulation jobs look for? The top searched job categories for Full Time Monte Carlo Simulation jobs are:
Full Time Monte Carlo Simulation jobs near you
Infographic showing various Full Time Monte Carlo Simulation job openings in the United States as of June 2026, with employment types broken down into 50% As Needed, and 50% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $67,601 per year, or $32.5 per hour.

Senior Quant Developer

Futran Tech Solutions Pvt. Ltd.

Remote

Full-time

Posted 26 days ago

Job description

Senior Quant Developer
Remote USA
Mandatory skills: Python OR C++, Monte Carlo simulation, quantitative background, derivatives pricing models and risk model back testing experience
Skills:
Minimum degree of Master or PhD in quantitative fields is required, with at least 3-5 years of relevant experience.
The candidate must have strong quantitative and analytical background with a solid theoretical foundation coupled with strong programming, documentation and communications skills.
Must have experience implementing complex market or credit risk quantitative modelling for OTC derivatives using programming languages (such as Python and C++) as well as mathematical/statistical software packages.
Knowledge of derivatives pricing models (Black Scholes, Hull White), Monte Carlo simulation, and risk model back testing experience is also a must.
Nice to have:
The candidate is preferred (a plus) to have experience in credit risk modelling and is familiar with credit risk concepts such as PFE (Potential Future Exposure), CSA, MPOR, collaterals IM and VM, and Monte Carlo simulation of long-time horizons.

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