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Remote Stochastic Modeling Jobs (NOW HIRING)

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 ...

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 ...

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 Aug 25, 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 August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 100% Remote job distribution, with an average salary of $83,896 per year, or $40.3 per hour.

Associate Actuary, Capital Modeling (REMOTE)

thg

Worcester, MA • On-site, Remote

Full-time

Posted 5 days ago

Job description

Our Corporate Actuarial department is seeking an Associate Actuary to join the Economic Capital Modeling team our Worcester, MA Corporate Headquarters or remote. 

POSITION SUMMARY:

This role supports the development, maintenance, and application of Hanover's Economic Capital Model (ECM) and related capital management tools. The ECM serves as a key decision-support framework for evaluating enterprise risk, capital requirements, risk-adjusted performance, reinsurance strategies, and strategic business opportunities.

Responsibilities include capital modeling, model validation, capital allocation analysis, profitability assessments, and evaluation of the impact of business and reinsurance strategies on enterprise risk and return.

This role partners with a variety of departments, including corporate finance, Reinsurance and Enterprise Risk Management. Strong analytical and communication skills are essential, as findings and recommendations will be presented to both technical and non-technical stakeholders. The position also contributes to ongoing model enhancements, process improvements, and the continued evolution of Hanover's capital management capabilities.

This is a Full-time, Exempt role.


IN THIS ROLE, YOU WILL: 

  • Support the maintenance, governance, and ongoing enhancement of Hanover's Economic Capital Model (ECM).
  • Analyze model assumptions, methodologies, and outputs, contributing recommendations that improve the ECM's effectiveness, accuracy, and business value.
  • Perform enterprise risk quantification, stochastic modeling, and capital adequacy analyses across underwriting, reserving, catastrophe, market, credit, and operational risks.
  • Conduct stress testing and scenario analyses to assess the impact of emerging risks and changing business conditions on capital requirements.
  • Analyze key drivers of economic capital consumption, profitability, and risk-adjusted performance across business segments.
  • Support the development and maintenance of capital allocation and performance measurement frameworks used in strategic decision-making.
  • Determine the impact of reinsurance structures, capital management initiatives, and business opportunities on risk, return, and capital efficiency.
  • Analyze the capital implications of strategic initiatives and management actions, providing data-driven insights and recommendations.
  • Partner with Finance, Enterprise Risk Management, Investments, Treasury, Pricing, Reserving, and business leaders to communicate results and support enterprise decision-making.

WHAT YOU NEED TO APPLY:

  • Bachelor's degree in a relevant technical or quantitative field.
  • Five+ years of actuarial, capital modeling, enterprise risk management, predictive analytics, pricing, reserving, or related analytical experience.
  • ACAS or equivalent experience preferred.
  • Strong understanding of actuarial modeling techniques, enterprise risk management concepts, and capital management principles.
  • Experience interpreting complex analytical results and translating them into business recommendations.
  • Advanced skills using Microsoft Office, including Excel and PowerPoint.
  • Programming and analytical experience using Python, R, SQL, and other actuarial or data analytics tools, with demonstrated ability to automate processes, develop analytical solutions, and improve operational efficiency
  • Proven ability to manage multiple priorities and deliver high-quality work within established timelines.
  • Ability to influence decisions and collaborate effectively across functions and organizational levels

Apply