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Stochastic Calculus Jobs (NOW HIRING)

Collabera LLC

Quantitative Analyst

Charlotte, NC · On-site

Strong mathematical background (Statistics, Stochastic Calculus, Financial Engineering) * Experience with exposure models (PFE/EPE/EAD) Note: The Company offers the following benefits for this ...

Collabera

Quantitative Analyst

Charlotte, NC · On-site

... Stochastic Calculus, Financial Engineering) Experience with exposure models (PFE/EPE/EAD) Note: The Company offers the following benefits for this position, subject to applicable eligibility ...

SaltHill Group

Commodity Quantitative Strategist

Houston, TX · On-site

$116K - $149K/yr

Experience with mathematical finance, derivatives, option pricing, and stochastic calculus. * Strong understanding of embedded optionality and drivers. * Minimum 2-7 years of professional experience ...

Wolverine Trading

C# Software Engineer

Chicago, IL · On-site

Required : • Strong foundation in advanced mathematics and statistics, including probability theory, stochastic calculus, numerical methods, and linear algebra • Experience with data analytic ...

Jefferies

Equity Derivatives Quant VP/SVP

Manhattan, NY · On-site

$175K - $300K/yr

Strong foundations in stochastic calculus, risk-neutral pricing and Greeks. * Knowledge of numerical solvers like Monte Carlo simulation (ideally including American Monte-Carlo) and PDE methods ...

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How much do stochastic calculus jobs pay per hour?

As of Jul 8, 2026, the average hourly pay for stochastic calculus in the United States is $25.08, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $28.61 per hour, depending on experience, location, and employer.

What are the common challenges faced by professionals working in stochastic calculus roles?

Professionals working with stochastic calculus often encounter challenges such as interpreting complex mathematical models, ensuring numerical stability in simulations, and translating theoretical results into practical applications. Given the abstract nature of stochastic processes, effective communication with colleagues from non-mathematical backgrounds can also be demanding. Additionally, staying up-to-date with new research and computational tools is essential, as the field constantly evolves, especially in finance and data science settings.

What is the difference between Stochastic Calculus vs Quantitative Analyst?

AspectStochastic CalculusQuantitative Analyst
Required CredentialsMathematics, Statistics, or Financial Engineering degreesMathematics, Statistics, Finance, or Economics degrees
Work EnvironmentResearch, modeling, and theoretical analysis in finance or engineeringDeveloping models, analyzing data, and supporting trading strategies
Industry UsageFinancial institutions, risk management, derivatives pricingInvestment banks, hedge funds, asset management firms

Stochastic Calculus focuses on the mathematical tools used to model randomness and uncertainty, essential for pricing derivatives and risk assessment. Quantitative Analysts apply these mathematical techniques, including stochastic calculus, to develop financial models, analyze markets, and inform trading decisions. While stochastic calculus provides the theoretical foundation, Quantitative Analysts utilize these methods in practical, industry-specific contexts.

What is stochastic calculus and what is it used for?

Stochastic calculus is a branch of mathematics that deals with integrating and differentiating functions that involve randomness, typically modeled by stochastic processes such as Brownian motion. It provides the mathematical foundation for modeling systems that evolve over time with inherent uncertainty, such as stock prices, interest rates, and physical processes influenced by random noise. Stochastic calculus is widely used in quantitative finance, engineering, physics, and other disciplines to analyze and predict dynamic systems where randomness plays a key role.

What are the key skills and qualifications needed to thrive as a professional specializing in stochastic calculus, and why are they important?

To excel in a role focused on stochastic calculus, you need advanced mathematical knowledge, particularly in probability theory, differential equations, and stochastic processes, usually supported by at least a master's or PhD in mathematics, statistics, or a related field. Familiarity with computational tools like MATLAB, Python (with libraries such as NumPy and SciPy), and specialized statistical software is typically required. Strong analytical thinking, problem-solving abilities, and attention to detail distinguish top professionals in this area. These skills are critical for accurately modeling and analyzing random systems, which underpin decision-making in finance, engineering, and scientific research.
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What job categories do people searching Stochastic Calculus jobs look for? The top searched job categories for Stochastic Calculus jobs are:
Stochastic Calculus jobs near you
Infographic showing various Stochastic Calculus job openings in the United States as of July 2026, with employment types broken down into 71% Full Time, and 29% Part Time. Highlights an 75% Physical, and 25% Remote job distribution, with an average salary of $52,166 per year, or $25.1 per hour.
Quantitative Analyst

Quantitative Analyst

Collabera LLC

Charlotte, NC • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Job description

Position Details:
Client: Banking
Job Title: Senior Quant Developer / Quantitative Modeler
Location: Hybrid role in Charlotte, NC 28202 (3 day onsite)
Schedule: Mon-Fri: Basic Business hours
Duration: 12 Months + Possible Extension
Start Date: ASAP - Apply Now !
Pay-range: 75-80/hr



Job Description:



  • This appears to be a Bank - Quantitative Analytics Specialist 4 (Contingent) opening focused on Counterparty Credit Risk (CCR) modeling, specifically cross-margin methodology development within Capital Markets.



Role Focus Area:



  • Counterparty Credit Risk modeling (not pricing models)

  • Cross-margin methodologies in prime brokerage/derivatives businesses

  • Quantitative model development and enhancement

  • Heavy Python development

  • Market risk modeling (VaR) without CCR exposure.

  • Pricing model development without margin methodology experience.

  • Pure Python development without quantitative finance.

  • Data science backgrounds lacking derivatives knowledge.



Skill Weighting (Very Important):



1.Cross-Margin Expertise 50%



  • Prime Brokerage margin methodologies

  • Cross-product margin offsets

  • Clearing/CCP margin concepts

  • Counterparty exposure management




  1. Mathematics & Quantitative Modeling 30%



  • Probability & Statistics

  • Stochastic Processes

  • Analytical formula derivation

  • Model validation and gap analysis




  1. Programming 20%



  • Python (expert)

  • SQL

  • AI coding tools (GitHub Copilot or similar)



Additional Details:



  • 5+ years in quantitative analytics

  • Counterparty Credit Risk experience

  • Prime Brokerage or Clearing experience

  • Cross-margin methodology knowledge

  • Advanced Python development skill

  • Strong mathematical background (Statistics, Stochastic Calculus, Financial Engineering)

  • Experience with exposure models (PFE/EPE/EAD)



Note: The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, (paid time , paid sick and safe time , hours of paid vacation time, weeks of paid parental leave, paid holidays annually - AS Applicable)

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