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Remote Stochastic Modeling Jobs (NOW HIRING)

Turing

Remote Quantitative Finance Analyst

Chicago, IL · Remote

$100 - $200/hr

Evaluate LLM models on quantitative finance topics such as stochastic modeling, derivatives pricing ... Fully remote and flexible work environment. * Competitive hourly compensation of ~$100+/hour ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... STAT 416 - Stochastic Modeling * STAT 418 - Introduction to Probability and Stochastic Processes ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... 416 - Stochastic Modeling/STAT 418 - Introduction to Probability and Stochastic Processes for ...

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$143K - $273K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Knowledge of stochastic modeling, machine learning, or other advanced mathematical techniques.

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$143K - $273K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Knowledge of stochastic modeling, machine learning, or other advanced mathematical techniques.

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$143K - $273K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Knowledge of stochastic modeling, machine learning, or other advanced mathematical techniques.

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How much do remote stochastic modeling jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for remote stochastic modeling in the United States is $40.33, according to ZipRecruiter salary data. Most workers in this role earn between $31.25 and $43.51 per hour, depending on experience, location, and employer.

What is remote stochastic modeling?

Remote stochastic modeling involves using mathematical and statistical techniques to analyze and predict outcomes that are inherently uncertain, all while working from a remote location. These models are widely used in fields such as finance, insurance, engineering, and data science to simulate complex systems and assess risks. As a remote stochastic modeler, professionals utilize specialized software and collaborate with teams online to develop, test, and interpret these models. This flexible work arrangement enables experts to contribute to projects from anywhere, making it ideal for those seeking work-life balance or international opportunities.

What are some common challenges faced by professionals in remote stochastic modeling roles, and how can they be addressed?

Professionals in remote stochastic modeling often encounter challenges such as collaborating effectively with geographically dispersed teams and ensuring consistent data access and version control. Clear communication and frequent virtual meetings are essential to align on model assumptions and share findings. Additionally, utilizing cloud-based collaboration tools and maintaining thorough documentation help streamline workflow and minimize misunderstandings. Staying proactive about seeking feedback and clarifications can also mitigate the isolation sometimes experienced in remote settings.

What are the key skills and qualifications needed to thrive as a remote stochastic modeler, and why are they important?

To thrive as a Remote Stochastic Modeler, you need a solid background in mathematics, probability theory, and statistical analysis, typically supported by a degree in mathematics, statistics, or a related field. Proficiency with programming languages like Python or R, experience with simulation software, and familiarity with data analysis tools are commonly required. Strong problem-solving abilities, attention to detail, and effective remote communication skills distinguish top performers in this role. These skills are crucial for developing accurate models and collaborating efficiently with distributed teams to solve complex, data-driven problems.

What is the difference between Remote Stochastic Modeling vs Remote Quantitative Analyst?

AspectRemote Stochastic ModelingRemote Quantitative Analyst
Required CredentialsAdvanced degrees in mathematics, statistics, or finance; programming skillsSimilar credentials; strong math, programming, and finance background
Work EnvironmentFinancial firms, hedge funds, risk management teams, often collaborativeFinancial institutions, investment firms, risk departments, often collaborative
Industry UsageUsed for developing models to predict market behavior and riskUsed for analyzing financial data, developing trading strategies, risk assessment
Comparison Search IntentUnderstanding modeling techniques in financeAnalyzing financial data and strategies

Remote Stochastic Modeling and Remote Quantitative Analyst roles share similar credentials and work environments, often within financial institutions. While stochastic modeling focuses on developing probabilistic models, quantitative analysts apply these models to analyze data and inform trading or risk decisions. Both roles are integral to financial analysis and often overlap in skills and industry usage.

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Remote Stochastic Modeling jobs near you
Infographic showing various Remote Stochastic Modeling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $83,896 per year, or $40.3 per hour.

CrossMargin Quantitative Model Developer

Charlotte, NC • On-site, Remote

Strategic Staffing Solutions
Professional, Scientific, and Technical Services • 201 - 500 employees
Learn more about Strategic Staffing Solutionsexternal

$80 - $101/hr

Full-time

Posted 11 days ago

Job description

Job Description Job Title: Cross-Margin Quantitative Model Developer - Hiring FAST. Industry: Finance Location: Charlotte, NC Pay Rate: $80-101HR on W2 Only - NO C2C Setting: Hybrid Required (Remote is NOT an Option) Duration: 12+ months Job ID: 247878 Required Qualifications: Python (expert level) - ability to build, structure, and maintain quant libraries. Experience using AI-assisted coding tools (Copilot or similar).

SQL expertise - ability to query and manipulate large datasets. Strong numerical skills and experience with stochastic modeling and capital markets models. Ability to derive mathematical formulas and implement them programmatically.

Strong understanding of crossmargining concepts in prime brokerage or derivatives clearing. Ability to identify and correct model gaps, inconsistencies, or legacy issues. Solid foundation in probability, statistics, and stochastic processes.

Desired Qualifications: Experience in prime brokerage or margin methodology design. Prior work with counterparty credit exposure models (e.g., PFE, EE, EAD). Familiarity with equities, commodities, energy, and structured derivative products

Responsibilities: Develop, enhance, and maintain counterparty credit risk models related to crossmargin methodologies. Derive analytical formulas, validate assumptions, and identify gaps in existing implementations. Improve or replace outdated models using modern stochastic and capital markets modeling techniques.

Support modeling across a range of complex financial products, including: Equity swaps Metals Energy derivatives Convertible bonds Lead the buildout and integration of Python-based quantitative libraries to support model development and validation activities. Produce robust prototype models and partner with technology teams to transition them into production. Utilize generative AI development tools (e.g., Copilot) to increase coding efficiency and automation

Collaborate on database queries using strong SQL expertise. Communicate clearly with model owners, business partners, technology teams, auditors, and project managers. Help translate business requirements into quant/model specifications and documentation.

Provide coaching and technical guidance to junior team members on both modeling and crossmargin concepts. Respond quickly to urgent model requests driven by high-impact crossmargin exposures in the CIB business. Ensure timely delivery of model enhancements, documentation, and validations.

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