ZipRecruiter

Log In

1

Quantitative Risk Jobs (NOW HIRING)

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

Job Summary We are seeking a Quantitative Risk Analyst to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and ...

State Street Global Advisors

Quantitative Risk

Boston, MA · Hybrid

$104K - $180K/yr

Quantitative Risk (State Street Bank And Trust Company; Boston, Massachusetts): This role will be part of the CMAO team focused on delivering modeling and analytics solutions to assess counterparty ...

Expand Energy

Quantitative Risk Analyst

Spring, TX

Job Summary We are seeking a Quantitative Risk Analyst to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and ...

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Job Summary We are seeking a Senior Quantitative Risk Manager to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and ...

State Street Corporation

Quantitative Risk

Boston, MA · On-site

$104K - $180K/yr

Quantitative Risk (State Street Bank And Trust Company; Boston, Massachusetts): This role will be part of the CMAO team focused on delivering modeling and analytics solutions to assess counterparty ...

Expand Energy

Quantitative Risk Manager

Spring, TX

Job Summary We are seeking a Senior Quantitative Risk Manager to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and ...

Wsfsbank

Quantitative Risk Analyst

Philadelphia, PA

$64K - $105K/yr

Key Responsibilities: * Assist the Quantitative Risk Manager in constructing a Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling ...

CoBank

Quantitative Risk Analyst

Greenwood Village, CO · On-site

$100 - $123/hr

Supports Quantitative Risk team and management during implementation of new models and/or research and development projects. * Provides analytic support for ad-hoc analysis and development of ...

New

WSFS Bank

Quantitative Risk Analyst

Philadelphia, PA · On-site

$64K - $105K/yr

Key Responsibilities: * Assist the Quantitative Risk Manager in constructing a Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling ...

WSFS Bank

Quantitative Risk Analyst

Philadelphia, PA · On-site

$64K - $105K/yr

Key Responsibilities: * Assist the Quantitative Risk Manager in constructing a Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling ...

next page

Showing results 1-20

All JobsFinance and Insurance JobsQuantitative Risk Jobs

quantitative risk information

See salary details

$31K

$90.6K

$146K

How much do quantitative risk jobs pay per year?

As of Aug 19, 2026, the average yearly pay for quantitative risk in the United States is $90,579.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $119,000.00 per year, depending on experience, location, and employer.

What is a quantitative risk analyst?

A Quantitative Risk Analyst is a finance professional who uses mathematical models and statistical techniques to assess and manage financial risks for organizations, particularly in banking, investment, and insurance sectors. They analyze data, develop risk models, and help companies make informed decisions to minimize potential losses. Their work involves programming, data analysis, and communicating complex risk scenarios to stakeholders. Quantitative Risk Analysts play a crucial role in ensuring that organizations remain financially stable and compliant with regulatory requirements.

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

To thrive as a Quantitative Risk Analyst, you need strong analytical skills, expertise in statistics and mathematics, and a relevant degree such as finance, mathematics, or engineering. Familiarity with statistical software (such as R, Python, or SAS), risk modeling tools, and industry certifications like FRM or CFA is highly valued. Excellent problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and convey insights to stakeholders. These competencies are crucial for accurately assessing risk, supporting strategic decisions, and ensuring the financial stability of organizations.

How do quantitative risk professionals typically collaborate with other departments within a financial institution?

Quantitative Risk professionals frequently work with various teams such as trading, portfolio management, compliance, and IT. This collaboration helps ensure that risk models accurately reflect real-world exposures and regulatory standards. Effective communication is key, as Quantitative Risk staff must translate complex data and models into actionable insights for non-technical stakeholders. Regular cross-departmental meetings and project-based collaborations are common, promoting a dynamic and integrated work environment.

What is the difference between Quantitative Risk vs Quantitative Analyst?

AspectQuantitative RiskQuantitative Analyst
Primary FocusAssessing and managing financial risks using quantitative methodsDeveloping models and strategies to analyze financial data and inform investment decisions
Required CredentialsOften requires risk management certifications (FRM, PRM), advanced degrees in finance, mathematics, or statisticsTypically requires degrees in finance, economics, mathematics, or related fields; certifications like CFA may be common
Work EnvironmentFinancial institutions, risk management departments, banksInvestment firms, hedge funds, banks, financial services companies

Quantitative Risk professionals focus on identifying and mitigating financial risks through specialized models, while Quantitative Analysts develop analytical models to support trading, investment, and financial decision-making. Both roles require strong quantitative skills and often similar educational backgrounds, but their core objectives differ: risk management versus financial analysis and strategy development.

How hard is it to become a quantitative risk?

Becoming a quantitative risk professional typically requires a strong background in mathematics, statistics, or finance, often supported by a relevant degree such as a master's or Ph.D. in a quantitative field. Developing skills in programming languages like Python or R and understanding financial models are also important, and obtaining certifications such as FRM or CFA can enhance job prospects. The role demands analytical ability, attention to detail, and the capacity to work with complex data sets, making it a challenging but attainable career path for those with the right skills and education.

How much do quantitative risk analysts make?

Quantitative risk analysts typically earn a median annual salary of around $80,000 to $120,000, depending on experience, education, and location. Senior analysts or those in high-demand financial centers can earn over $150,000, often supplemented by bonuses and benefits. Strong skills in statistics, programming, and risk modeling tools are essential for higher compensation.
More about quantitative risk jobs

What cities are hiring for Quantitative Risk jobs?

Cities with the most Quantitative Risk job openings:

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

The most popular types of Quantitative Risk jobs are:

What states have the most Quantitative Risk jobs?

States with the most job openings for Quantitative Risk jobs include:

What job categories do people searching Quantitative Risk jobs look for?

The top searched job categories for Quantitative Risk jobs are:

quantitative risk jobs near you
Infographic showing various Quantitative Risk 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 $90,579 per year, or $43.5 per hour.

Quantitative Risk Analyst

Expand Energy

Spring, TX • On-site

Full-time

Re-posted 13 hours ago

Job description

Our core values - Stewardship, Character, Collaborate, Learn, Disrupt - are the lens through which we evaluate every business decision. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expand's performance among our E&P competitors.
We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply. If you meet any combination of our requirements, we encourage you to apply. We strive to hire people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger.
Job Summary
We are seeking a Quantitative Risk Analyst to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and related structured/optional physical and financial transactions in a commodity trading business. The role will partner closely with trading, structuring, origination, middle office, risk, technology, and finance to deliver decision-quality analytics, robust model governance, and scalable reporting.
This role is designed for a candidate who combines cross-commodity quantitative rigor in their quantitative risk leadership with practical energy trading valuation and risk-control orientation.
Job Duties & Responsibilities
1) Quantitative Modeling, Valuation, and Analytics
  • 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 optional and structured transactions, including storage, transport, tolling, heat-rate optionality, basis/spread structures, swing optionality, and other asset-backed or logistics-driven exposures.
  • Support mark-to-market, fair value, forward curve construction, volatility surfaces, scenario analysis, and P&L attribution for complex positions and portfolios.
  • Design and improve analytical frameworks for VaR, Expected Shortfall, stress testing, backtesting, component risk, sensitivity analysis, and scenario analysis.

2) Trading and Commercial Support
  • Partner directly with traders, originators, and structurers to evaluate transactions, challenge assumptions, explain model outputs, and support hedging and optimization decisions.
  • Translate market views, deal structures, and operational realities into actionable analytics that support commercial decisions across gas, LNG, and power.
  • Provide analysis of risk drivers, spread movements, optionality value, and changes in valuation or risk metrics to risk committees and senior leadership.

3) Risk Framework, Controls, and Governance
  • Strengthen the quantitative underpinnings of the firm's market risk framework, including model documentation, assumptions governance, testing standards, and auditability.

4) Systems, Data, and Automation
  • Build or enhance scalable analytics in Python and related tools to automate recurring calculations, improve transparency, and reduce manual risk processes.
  • Work with ETRM/CTRM systems and market data infrastructure to ensure robust integration of curves, positions, valuation logic, and risk outputs. Experience with systems such as Endur, Allegro, ZEMA, or comparable platforms is valuable.

Create reports, dashboards, and visualizations that communicate complex quantitative results clearly to both technical and non-technical stakeholders.
Job Specific Skills
Technical Skills
  • Advanced Python skills for quantitative analytics, risk engines, data pipelines, and automated reporting; familiarity with pandas, NumPy, SciPy, and production-quality coding practices is expected.
  • Additional programming capability in one or more of SQL, C#, C++, VBA, or similar languages.
  • Strong understanding of probability, statistics, stochastic modeling, option pricing, numerical methods, Monte Carlo simulation, and time-series analysis.
  • Experience with data visualization and reporting tools and the ability to present quantitative insights clearly to senior stakeholders.
  • Practical use of AI-enabled tools to accelerate coding, research, workflow automation, data exploration, or insight generation, with appropriate controls for model risk, reproducibility, and governance.
  • Familiarity with Git/GitHub/GitLab, software lifecycle controls, and documentation standards is highly desirable.

Education
  • Bachelor's degree from an accredited University required in a quantitative discipline such as Mathematics, Statistics, Physics, Engineering, Computer Science, Econometrics, Finance, Applied Economics or related.
  • Master's degree or PhD preferred in a quantitative discipline such as Mathematics, Statistics, Physics, Engineering, Computer Science, Econometrics, Finance, Applied Economics or related.

Experience
  • Experience in quantitative risk, quantitative analytics, structuring, valuation, or model development in a Master's or PhD program focusing on commodity trading, energy trading, merchant energy, utility trading, hedge fund, or investment banking environment.
  • Demonstrated hands-on experience modeling optionality of complex and / or dynamical systems.

Preferred Experience / Strong Pluses
  • Understanding of both physical and financial commodity markets, including forwards, swaps, options, structured transactions, and asset-backed exposures a plus.
  • Experience with market risk metrics, including VaR/GMaR/EaR/stress/scenario frameworks, and the ability to explain risk in a trading context rather than only from a theoretical perspective.
  • Experience in asset-backed trading, including storage, transport, generation, renewables, batteries, or tolling structures in North America gas markets.
  • Experience spanning both financial trading and physical energy trading, especially where the role bridged derivatives pricing with logistics, dispatch, storage, or LNG optionality.
  • Model validation, model governance, or formal model review experience.
  • Exposure to LNG portfolio modeling, shipping/scheduling optionality, or international gas/LNG valuation frameworks.
  • Experience supporting power market analytics such as nodal pricing, CRRs/FTRs, heat-rate modeling, dispatch logic, congestion analysis, or ISO/RTO market behavior.

Additional Qualifications
Core Competencies
  • Ability to do independent research and apply theoretical techniques to real world problems.
  • Clear communicator who can explain complex model behavior, assumptions, and limitations to traders, risk managers, finance, and executives.
  • High standards for accuracy, transparency, governance, and documentation.
  • Comfortable operating in a fast-moving, front-office-adjacent trading environment where priorities evolve and analytics must be both rigorous and timely.

Expand Energy takes necessary action to ensure that all applicants are treated without regard to their race, color, religion, sex, sexual orientation, age, gender identity, national origin, genetic information, disability, pregnancy, military or veteran status or any other protected characteristic as established by law.
Expand Energy Corporation's operations are focused on discovering and developing its large and geographically diverse resource base of unconventional oil and natural gas assets onshore in the United States.

Apply