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Intern Quantitative Risk Modeler Jobs (NOW HIRING)

Quanta Search

Quantitative Risk Analyst

Manhattan, NY · On-site

Quantitative Risk Analysts perform research to identify opportunities for improved risk management ... Evaluate and validate price and risk models to ensure the soundness and correct application of the ...

Quanta Search

Quantitative Risk Analyst

Manhattan, NY · On-site +1

Quantitative Risk Analysts perform research to identify opportunities for improved risk management ... Evaluate and validate price and risk models to ensure the soundness and correct application of the ...

Gunvor

Quantitative Risk Analyst

Houston, TX

Take ownership of model(s) including accurate position assessment with understanding of contract maturity behavior and seasonality. Streamline and improve processes such as data quality checks and ...

Gunvor

Quantitative Risk Analyst

Houston, TX · On-site

Main Responsibilities • Develop and implement quantitative risk models and metrics for trading operations. • Take ownership of model(s) including accurate position assessment with understanding ...

Ryan Specialty

Quantitative Risk Modeling Lead

Position Summary As a Quantitative Risk Modeling Led in the Ryan Credit Solutions department at Ryan Specialty, you will leverage your actuarial and quantitative expertise to shape the underwriting ...

Wsfsbank

Quantitative Risk Analyst

Philadelphia, PA

$64K - $105K/yr

NewLane Finance is seeking an individual to assist the credit and risk modeling and analytics ... This role will be responsible for providing analytical/quantitative input to help develop ...

WSFS Bank

Quantitative Risk Analyst

Philadelphia, PA · On-site

$64K - $105K/yr

NewLane Finance is seeking an individual to assist the credit and risk modeling and analytics ... This role will be responsible for providing analytical/quantitative input to help develop ...

WSFS Bank

Quantitative Risk Analyst

Philadelphia, PA

$64K - $105K/yr

NewLane Finance is seeking an individual to assist the credit and risk modeling and analytics ... This role will be responsible for providing analytical/quantitative input to help develop ...

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

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How much do intern quantitative risk modeler jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for intern quantitative risk modeler in the United States is $18.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $19.23 per hour, depending on experience, location, and employer.
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Intern Quantitative Risk Modeler jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 2 days ago

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)