1

Quant Analytics Jobs in Houston, TX (NOW HIRING)

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 ...

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 ...

Familiarity with machine learning techniques, advanced forecasting methodologies, and quantitative analytics frameworks. * Experience with cloud-based analytics platforms, modern data architectures ...

Familiarity with machine learning techniques, advanced forecasting methodologies, and quantitative analytics frameworks. * Experience with cloud-based analytics platforms, modern data architectures ...

Showing results 21-40

Quant Analytics information

See Houston, TX salary details

$50.1K

$113.8K

$187.7K

How much do quant analytics jobs pay per year?

As of Aug 13, 2026, the average yearly pay for quant analytics in Houston, TX is $113,800.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $145,600.00 per year, depending on experience, location, and employer.

What is the difference between Quant Analytics vs Data Analyst?

AspectQuant AnalyticsData Analyst
Required CredentialsDegree in finance, mathematics, or related fields; often requires programming skillsDegree in statistics, business, or related fields; may require basic programming knowledge
Work EnvironmentFinancial firms, hedge funds, investment banksCorporate, marketing, healthcare, and other industries
Job FocusDeveloping complex models for trading and risk managementInterpreting data to inform business decisions and reporting

Quant Analytics professionals focus on building advanced financial models and algorithms primarily in finance and trading environments. Data Analysts interpret and visualize data to support business strategies across various industries. While both roles involve data handling, Quant Analytics emphasizes quantitative modeling and programming, whereas Data Analysts focus on data interpretation and reporting.

What are the key skills and qualifications needed to thrive as a quant analytics professional?

To thrive in Quant Analytics, you need strong quantitative skills, advanced knowledge of mathematics and statistics, and often a degree in fields like mathematics, physics, engineering, or finance. Familiarity with programming languages such as Python, R, or MATLAB, as well as experience with data analysis tools and financial modeling software, is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and conveying insights to stakeholders. These skills and qualities are vital for developing robust quantitative models that support informed decision-making in fast-paced financial environments.

What is a quant analytics professional?

Quant Analytics, short for quantitative analytics, refers to the use of mathematical models, statistical methods, and computational techniques to analyze financial data and inform investment decisions. Professionals in this field, known as quantitative analysts or 'quants,' develop and implement algorithms for risk management, pricing, trading strategies, and portfolio management. Quant Analytics is widely used in banks, hedge funds, and investment firms to gain insights from large data sets and optimize financial performance. The role typically requires strong skills in mathematics, programming, and finance.

What does a quant analytics do?

A quant analyst, or quantitative analyst, develops mathematical models and uses statistical techniques to analyze financial data and inform investment decisions. They often work with programming languages like Python or R and tools such as Excel or specialized software to identify trends, assess risks, and optimize trading strategies.

How do quant analytics professionals typically collaborate with other teams within a financial institution?

Quant Analytics professionals often work closely with traders, risk managers, and software engineers to develop, implement, and refine quantitative models. They translate complex data into actionable insights, which may influence trading strategies or risk assessment. Effective communication and teamwork are essential, as quants must present their findings in a way that is understandable and useful to non-technical stakeholders. Collaboration is usually facilitated through regular meetings, code reviews, and joint problem-solving sessions.
What cities near Houston, TX are hiring for Quant Analytics jobs? Cities near Houston, TX with the most Quant Analytics job openings:
Infographic showing various Quant Analytics job openings in Houston, TX as of July 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $113,800 per year, or $54.7 per hour.

Quantitative Risk Manager

Expand Energy

Spring, TX โ€ข On-site

Full-time

Re-posted 24 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 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 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.
  • Lead or support model review, model validation readiness, model governance, and remediation of model limitations and control gaps.
  • Ensure analytics and reporting align with board-approved risk tolerances, internal policies, and evolving control requirements.

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
  • 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 commodity trading, energy trading, merchant energy, utility trading, hedge fund, or investment banking environment.
  • Demonstrated hands-on experience modeling, valuing, and risk assessing instruments and portfolios in natural gas, LNG, and power.
  • Strong understanding of both physical and financial commodity markets, including forwards, swaps, options, structured transactions, and asset-backed exposures.
  • 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.
  • Proven success working cross-functionally with front office, risk, operations, finance, and technology teams.

Preferred Experience / Strong Pluses
  • 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.
  • Ability to mentor junior analysts and influence standards for quantitative methods across the organization.

Additional Qualifications
Core Competencies
  • Strong commercial judgment with the ability to connect quantitative outputs to real trading decisions.
  • 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.