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Associate Quantitative Risk Analyst Jobs in Texas

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 ...

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 ...

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Design and improve analytical frameworks for VaR, Expected Shortfall, stress testing, backtesting ... Strengthen the quantitative underpinnings of the firm's market risk framework, including model ...

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Design and improve analytical frameworks for VaR, Expected Shortfall, stress testing, backtesting ... Strengthen the quantitative underpinnings of the firm's market risk framework, including model ...

Bank OZK

Associate, Quantitative Modeling

Dallas, TX

... Analysis and Review - CCAR - protocols). Also develops and documents the quantitative tools used to quantify credit risk, provide early identification of trends in compliance activities, and support ...

Bank OZK

Associate, Quantitative Modeling

Dallas, TX · On-site

... Analysis and Review - CCAR - protocols). Also develops and documents the quantitative tools used to quantify credit risk, provide early identification of trends in compliance activities, and support ...

Aramco

Market Risk Analyst

Houston, TX · On-site

Collaborate with quantitative analysts to refine model assumptions, validate model outputs, and ensure accuracy in risk measurement. * Apply advanced statistical techniques and machine learning ...

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Associate Quantitative Risk Analyst information

What is an associate quantitative risk analyst?

Associate Quantitative Risk Analysts are entry- to mid-level professionals who help financial institutions and organizations assess and manage risk using mathematical models and statistical techniques. They analyze data to identify potential risks, develop risk management strategies, and support decision-making processes. Their work often involves using quantitative software, working with large datasets, and collaborating with other risk management and finance professionals. Typically, they have backgrounds in mathematics, statistics, finance, or related fields.

What are the key skills and qualifications needed to thrive as an associate quantitative risk analyst?

To thrive as an Associate Quantitative Risk Analyst, you need a strong background in mathematics, statistics, finance, and data analysis, typically supported by a relevant degree such as in finance, mathematics, or economics. Familiarity with statistical software (like R, SAS, or Python), financial modeling tools, and possibly certifications such as FRM or CFA is highly valuable. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and presenting findings. These competencies are essential for accurately assessing financial risks and supporting informed decision-making in risk management environments.

What are some common challenges faced by associate quantitative risk analysts in their first year, and how can they overcome them?

In their first year, Associate Quantitative Risk Analysts often encounter challenges such as adapting to complex financial models, learning to interpret large datasets, and effectively communicating technical findings to non-technical stakeholders. Navigating regulatory requirements and understanding the company's risk management framework can also be demanding. To overcome these obstacles, new analysts should proactively seek mentorship, participate in team discussions, and leverage internal training resources to build both technical and soft skills. Regular collaboration with colleagues in risk, finance, and IT departments can also provide valuable insights and accelerate professional growth.

What is the difference between Associate Quantitative Risk Analyst vs Credit Risk Analyst?

AspectAssociate Quantitative Risk AnalystCredit Risk Analyst
Required CredentialsBachelor's in finance, economics, or related field; often some familiarity with quantitative methodsBachelor's in finance, economics, or related field; certifications like CFA or FRM are common
Work EnvironmentFinancial institutions, risk management teams, quantitative departmentsBanking, lending institutions, credit departments
Employer & Industry UsageUsed in risk modeling, data analysis, and quantitative assessmentsFocuses on assessing creditworthiness and loan risk

The Associate Quantitative Risk Analyst primarily focuses on developing models and analyzing data to measure financial risks, often working with quantitative tools. In contrast, a Credit Risk Analyst concentrates on evaluating the creditworthiness of borrowers and managing credit risk. While both roles require similar educational backgrounds and work within financial institutions, their core responsibilities differ—one emphasizes quantitative modeling, the other credit assessment.

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

The most popular types of Quantitative Risk Analyst jobs in Texas are:

What are popular job titles related to Associate Quantitative Risk Analyst jobs in Texas?

For Associate Quantitative Risk Analyst jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Associate Quantitative Risk Analyst jobs in Texas look for?

The top searched job categories for Associate Quantitative Risk Analyst jobs in Texas are:

What cities in Texas are hiring for Associate Quantitative Risk Analyst jobs?

Cities in Texas with the most Associate Quantitative Risk Analyst job openings:

Associate Quantitative Risk Analyst jobs near you

Quantitative Risk Analyst

Expand Energy

Spring, TX • On-site

Full-time

Re-posted 2 days 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.

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