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Temp Monte Carlo Simulation Jobs (NOW HIRING)

Citigroup

Rates XVA Quant

Manhattan, NY · On-site

Implement Monte Carlo simulation and exposure modeling to support valuation and counterparty risk analytics * Contribute to the full model lifecycle - from research and implementation through to ...

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Temp Monte Carlo Simulation information

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$11K

$67.6K

$121.5K

How much do temp monte carlo simulation jobs pay per year?

As of Jul 7, 2026, the average yearly pay for temp 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 the difference between Temp Monte Carlo Simulation vs Temp Data Analyst?

AspectTemp Monte Carlo SimulationTemp Data Analyst
Required CredentialsKnowledge of probability, statistics, and simulation softwareProficiency in data analysis, Excel, SQL, and statistical tools
Work EnvironmentProject-based, often in finance, engineering, or risk managementOffice setting, analyzing datasets across various industries
Employer & Industry UsageUsed in finance, engineering, and risk assessment firmsCommon in finance, marketing, healthcare, and tech companies

Temp Monte Carlo Simulation focuses on modeling uncertainty and risk analysis using simulation techniques, while Temp Data Analyst interprets data to inform business decisions. Both roles require analytical skills but differ in tools and application areas.

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Temp Monte Carlo Simulation jobs near you

AI System Analyst (AI Monte Carlo)

Saransh Inc

Houston, TX • On-site

Contractor

Posted 14 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