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Risk Modeling Intern Jobs (NOW HIRING)

Concord Advice

Data Scientist - Intern

Florham Park, NJ · On-site

$40K - $70K/yr

Data Scientist Intern -- Concord AdviceSummary Concord Advice is a dynamic fintech company ... Exposure to credit underwriting or risk modeling within a lending business. Compensation & Benefits

Deloitte

Du mochtest im Bereich Strategy, Risk & Transactions - Advisory - Valuation & Modeling ... Als Praktikant Valuation & Modeling (m/w/d) hilfst du bei Projekten, in denen verschiedene ...

Tenaska

Market Risk Intern - Year-Round Opportunity

Omaha, NE · On-site

$13.50 - $18.25/hr

Through hands-on research, analysis, reporting, and project support, the intern will gain practical experience in statistical and financial modeling, valuation, risk management, and broader business ...

Kohl's

Credit Risk Intern About the Role As Credit Risk Analyst II Intern, you will conduct ad-hoc ... Develop forecasting revenue models - for interest, fees & outstanding - dollars and units.

Grant Thornton

Risk Advisory Intern - Summer 2027

Chicago, IL · On-site

$15.50 - $20.50/hr

As a Risk Intern your primary responsibility will be executing high quality Risk projects and ... models to evaluate data, costs and benefits * Evaluate and test IT controls and identify areas of ...

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How much do risk modeling intern jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for risk modeling intern in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What does a risk modeling intern do?

A Risk Modeling Intern assists in analyzing and quantifying financial risks for an organization by using statistical models and data analysis techniques. Their tasks may include data collection, cleaning, and processing, as well as building or testing predictive models to assess potential risks. They often work closely with senior risk analysts or modelers, helping to interpret data and generate reports. The internship provides hands-on experience in risk management, finance, and analytics, which are valuable for a future career in these fields.

What types of projects does a risk modeling intern typically work on, and how do these contribute to the team's objectives?

Risk Modeling Interns commonly support the development and validation of quantitative models used to assess financial, credit, market, or operational risks. They may assist in data collection, statistical analysis, and model documentation, often working closely with experienced analysts and modelers. These projects directly contribute to the team's goal of ensuring models are robust, accurate, and compliant with regulatory standards. Interns gain hands-on experience with industry-standard tools and methodologies, helping the team make informed decisions about risk management.

What are the key skills and qualifications needed to thrive as a risk modeling intern, and why are they important?

To excel as a Risk Modeling Intern, you need a strong background in quantitative analysis, statistics, and finance, often supported by coursework in mathematics, economics, or data science. Familiarity with programming languages like Python or R, statistical modeling tools, and Excel is typically required, and knowledge of industry-standard software such as SAS or MATLAB is valuable. Strong analytical thinking, attention to detail, and effective communication skills help you interpret data and present findings clearly. These abilities are essential for accurately assessing risk, supporting decision-making, and contributing to the success of financial or business risk management teams.
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Risk Modeling Intern jobs near you
Infographic showing various Risk Modeling Intern job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Cambridge, MA • On-site

Risk Analytics Company
See more jobs at Risk Analytics Companyexternal

Full-time

Re-posted 6 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)