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Full Time Risk Quant Jobs (NOW HIRING)

MBP

Construction Project Risk Consultant (Full-Time)

$94K - $114K/yr

MBP is looking for a project risk consultant to support qualitative and quantitative risk ... Status: Full-time The base salary range for this position is $94,000.00 to $114,000.00. Actual ...

Jaquith Consulting Group Inc

Risk Manager

Sacramento, CA · On-site

$110K - $165K/yr

... Full-Time Position Summary Jaquith Consulting Group, Inc. (JCG) is seeking an experienced Risk ... Facilitate and support regular qualitative and quantitative risk assessments, including ...

Pavago

Risk Analyst

Risk Analyst / Risk Manager Position Type: Full-Time, Remote Working Hours: U.S. client business ... The ideal candidate combines strong analytical and quantitative skills with excellent communication ...

IMC

Experienced Risk Manager

Chicago, IL · On-site

$150K - $210K/yr

You'll collaborate daily with traders, quantitative researchers, and software engineers while ... Base salary is only one component of total compensation; all full-time, permanent positions are ...

Invesco

Risk Manager

New York, NY · Hybrid

$150K - $165K/yr

Bachelors or Masters degree in a quantitative field such as quantitative finance, statistics ... Full time Worker Type Employee Job Exempt (Yes / No) Yes Workplace Model Pursuant to Invesco ...

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Full Time Risk Quant information

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$98K

$169.7K

$259.5K

How much do full time risk quant jobs pay per year?

As of Aug 21, 2026, the average yearly pay for full time risk quant in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Risk Quant vs Quantitative Analyst?

AspectFull Time Risk QuantQuantitative Analyst
Required CredentialsAdvanced degrees in finance, mathematics, or related fields; certifications like CFA or FRMSimilar educational background; often CFA or FRM beneficial
Work EnvironmentFinancial institutions, risk management teams, trading floorsInvestment banks, asset management firms, hedge funds
Employer & Industry UsagePrimarily in risk management departments within financeAcross various finance sectors including trading, investment analysis
Comparison Search IntentUnderstanding risk-focused roles in financeAnalyzing financial data and models for investment decisions

Full Time Risk Quants focus on assessing and managing financial risks using quantitative models within risk management teams. Quantitative Analysts, while similar, often have a broader role in developing models for trading, investment strategies, or financial analysis. Both roles require strong quantitative skills and relevant certifications, but their primary focus and work environments differ slightly.

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What are the most commonly searched types of Risk Quant jobs?

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Full Time Risk Quant jobs near you
Infographic showing various Full Time Risk Quant job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 16 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)