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Entry Level Monte Carlo Simulation Jobs (NOW HIRING)

AllRight Jobs Inc

Python Developer ARJ/118

Houston, TX · On-site

$90 - $95/hr

... Monte Carlo simulations and risk-focused data analysis. - Responsible for translating analytical findings into clear visualizations and dashboards. - Collaborate with data analytics leads and risk ...

Judge Group, Inc.

Configuration Management

Sunnyvale, CA · On-site

$75 - $85/hr

Coordinate pipelines, automated test execution, and Monte Carlo simulation runs on large-scale compute clusters. * Apply industry standards, processes, procedures, and tools consistently across the ...

KBR, Inc.

Jr Cost Analyst

Chantilly, VA · On-site

Proficient with the application of Monte Carlo simulation techniques * Excellent communication skills with the ability to present results to senior leadership * Ability to work independently and lead ...

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How much do entry level monte carlo simulation jobs pay per year?

As of Jun 1, 2026, the average yearly pay for entry level 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 as an Entry Level Monte Carlo Simulation analyst, and why are they important?

To thrive as an Entry Level Monte Carlo Simulation analyst, you need a solid background in mathematics, probability, and statistics, often supported by a degree in a quantitative field such as mathematics, engineering, or physics. Familiarity with programming languages like Python or R and simulation software such as MATLAB or @RISK is typically required. Analytical thinking, attention to detail, and effective communication are important soft skills for interpreting results and collaborating with teams. These skills ensure accurate modeling, insightful analysis, and clear reporting of simulation outcomes for data-driven decision-making.

What are some typical projects or tasks that an Entry Level Monte Carlo Simulation professional can expect to work on?

As an Entry Level Monte Carlo Simulation professional, you will likely assist in developing, running, and analyzing simulations to model uncertainty and predict outcomes for projects such as financial forecasting, engineering design, or risk assessment. Your daily tasks might include preparing input data, coding simulation scripts (often in Python or MATLAB), and interpreting simulation results under the guidance of senior analysts. You'll also collaborate with cross-functional teams—such as data scientists, engineers, or financial analysts—to ensure your simulations align with project goals and client needs. This hands-on experience provides a strong foundation for career growth in modeling, analytics, or advanced quantitative roles.

What are Entry Level Monte Carlo Simulation jobs?

Entry level Monte Carlo Simulation jobs involve using probabilistic modeling and computational techniques to simulate complex systems and processes. Professionals in these roles typically assist in running simulations, analyzing results, and supporting research or decision-making in fields like finance, engineering, or data science. With guidance from senior staff, entry-level employees are expected to have a basic understanding of probability, statistics, and programming languages such as Python or R. These positions are ideal for recent graduates or those new to the field who are looking to apply mathematical and analytical skills in a practical setting.

What is the difference between Entry Level Monte Carlo Simulation vs Entry Level Data Analyst?

AspectEntry Level Monte Carlo SimulationEntry Level Data Analyst
Required CredentialsBachelor's in Math, Statistics, or related field; basic programming skillsBachelor's in Data Science, Statistics, or related field; proficiency in Excel and SQL
Work EnvironmentFinancial, insurance, or engineering firms; analytical teamsBusiness, marketing, finance, or tech companies; data teams
Industry UsageRisk analysis, financial modeling, simulationsData interpretation, reporting, business insights

Entry Level Monte Carlo Simulation focuses on probabilistic modeling and risk assessment using simulations, often requiring programming skills. Entry Level Data Analysts interpret data, create reports, and support decision-making. While both roles involve data handling, Monte Carlo roles emphasize simulation techniques, whereas Data Analysts focus on data visualization and analysis.

More about Entry Level Monte Carlo Simulation jobs
What cities are hiring for Entry Level Monte Carlo Simulation jobs? Cities with the most Entry Level 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 Entry Level Monte Carlo Simulation jobs? States with the most job openings for Entry Level Monte Carlo Simulation jobs include:
What job categories do people searching Entry Level Monte Carlo Simulation jobs look for? The top searched job categories for Entry Level Monte Carlo Simulation jobs are:
Entry Level Monte Carlo Simulation jobs near you
Infographic showing various Entry Level Monte Carlo Simulation job openings in the United States as of May 2026, with employment types broken down into 20% Locum Tenens, 13% As Needed, 7% Full Time, 4% Part Time, 51% Temporary, and 5% Contract. Highlights an 100% Physical job distribution, with an average salary of $67,601 per year, or $32.5 per hour.
Principal Software Engineer - Circuit Simulation R&D

Principal Software Engineer - Circuit Simulation R&D

Cadence Inc

San Jose, CA • On-site, Remote

$136.50K - $253.50K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago

Job description

Graduate Researcher-Practitioner in Applied Mathematics/Statistics

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology. We seek a graduate researcher-practitioner in applied mathematics/statistics to advance algorithms for electronic circuit simulation, Monte Carlo yield analysis, and optimization. You will work cross-functionally to turn deep math into production-grade technology.

Qualifications
  • Graduate degree in applied mathematics, statistics, or a closely related field (CS with strong math focus).
  • Demonstrated ability to conduct literature reviews, translate theory to practice, and deliver innovative results in real-world settings.
Core Expertise
  • Statistical inference: significance testing (p-values, confidence intervals), Bayesian statistics, design of experiments, Monte Carlo methods (random sampling, density estimation).
  • Rare-event and reliability analysis (a plus): importance sampling, subset simulation, cross-entropy methods, extreme value/tail modeling, yield estimation.
  • Surrogate modeling and Uncertainty Quantification (a plus): Gaussian processes, polynomial chaos, sparse grids, variance reduction.
Applied Mathematics (any of the following is a plus)
  • Optimization: linear, nonlinear, convex, integer, stochastic, variational; robust/multi-objective; derivative-free/global methods (e.g., CMA-ES, Bayesian optimization).
  • Numerical analysis: numerical linear algebra (sparse/Krylov/preconditioning), stiff ODE/DAE solvers, approximation, quadrature; model reduction (POD/MOR).
  • Differential equations: ODE/PDE/SDE, dynamical systems.
  • Probability and statistics: stochastic processes, inference, uncertainty quantification.
  • Data science: statistical learning, optimization for ML, dimensionality reduction.
Familiarity with Machine Learning (preferred)
  • Classical ML: regression (linear/logistic), regularization (ridge/lasso), classification (SVM, kNN), ensembles (trees, random forests, boosting).
  • Contemporary AI (a plus): graph neural networks, transformers, reinforcement/transfer learning, representation learning, active learning.
Software and Systems (Not needed but any of the following is a plus)
  • Programming proficiency in Python and/or C++ is a plus (NumPy/SciPy, PyTorch/JAX, performance optimization, clean APIs).
  • Strong computer science background is a plus (data structures, algorithms, version control, testing, CI/CD).
  • HPC/parallel computing (a plus): MPI, CUDA, distributed workflows.
Any prior Experience in the following areas is a plus
  • Scientific computing in one or more areas: computational electromagnetics, fluid/thermal/molecular dynamics, computational physics, or electrical circuit simulation.
  • Electronic design automation (EDA): SPICE/Spectre/Verilog-A, netlists, PVT/Monte Carlo flows, yield/parametric corners.
Responsibilities
  • Research, design, and validate algorithms for circuit simulation, rare-event estimation, and optimization.
  • Quantify accuracy/speed vs. baselines; perform rigorous statistical analyses.
  • Build robust, maintainable implementations and integrate with production toolchains.
  • Good Team Player as well as collaborate with cross-functional teams and document methods and results clearly.

The annual salary range for California is $136,500 to $253,500. You may also be eligible to receive incentive compensation: bonus, equity, and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the salary range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.

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