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Quantitative Modeling Jobs in Houston, TX (NOW HIRING)

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

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 ...

Expand Energy

Quantitative Risk Manager

Spring, TX

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 ...

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

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 ...

Expand Energy

Quantitative Risk Analyst

Spring, TX

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 ...

ExxonMobil

Natural Gas Modeling Analyst

Spring, TX · On-site

We are seeking a highly motivated analyst with deep expertise in natural gas fundamentals, quantitative modeling, and GPCM (Gas Pipeline Competition Model) to develop and enhance analytical ...

iShare Inc

SENIOR MODELING LEAD

Houston, TX · On-site

Hands on experience in Model Development, Model Monitoring of advanced ML/quantitative/finance models * Strong proficiency in Python; familiarity with modern AI/ML frameworks, ML-Ops, and large-scale ...

ExxonMobil

Natural Gas Modeling Analyst

Spring, TX

We are seeking a highly motivated analyst with deep expertise in natural gas fundamentals, quantitative modeling, and GPCM (Gas Pipeline Competition Model) to develop and enhance analytical ...

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All JobsQuantitative Modeling JobsQuantitative Modeling Jobs in Houston, TX

Quantitative Modeling information

See Houston, TX salary details

$93.6K

$162.1K

$247.8K

How much do quantitative modeling jobs pay per year?

As of Aug 3, 2026, the average yearly pay for quantitative modeling in Houston, TX is $162,086.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,400.00 and $190,000.00 per year, depending on experience, location, and employer.

What is a quantitative modeler?

A quantitative modeler is a professional who develops mathematical and statistical models to analyze financial data, assess risk, and support decision-making in finance or related fields. They often use programming languages like Python or R and have strong skills in mathematics, statistics, and data analysis. These models help organizations optimize strategies and manage uncertainties effectively.

What jobs pay 500,000 a year in the US?

In quantitative modeling, senior roles such as quantitative analysts, quantitative traders, and hedge fund managers can earn $500,000 or more annually, especially with bonuses and profit sharing. These positions typically require advanced degrees, strong programming skills, and experience in financial markets or risk management.

What are typical daily tasks and projects for someone in a Quantitative Modeling role?

In a Quantitative Modeling position, your daily activities usually include analyzing large datasets, building and validating predictive models, and developing algorithms to solve business or financial problems. You might spend time coding, running simulations, and interpreting model outputs to inform strategy or risk assessment. Collaboration is common—you'll often work with data scientists, business analysts, or subject matter experts to refine models and ensure they're aligned with organizational goals. The work is intellectually stimulating and fast-paced, with opportunities to see your analytical insights directly impact decision-making.

What job makes $1,000,000 a year?

In quantitative modeling, high-level roles such as senior quantitative analysts, hedge fund managers, or chief investment officers can earn $1,000,000 or more annually, especially with bonuses and profit sharing. These positions typically require advanced degrees, strong analytical skills, and experience in finance, data analysis, or risk management.

What is the highest paid modeling job?

In quantitative modeling, senior roles such as Quantitative Research Director or Head of Quantitative Strategies tend to have the highest salaries, often exceeding $200,000 annually, especially in major financial centers. These positions require advanced skills in mathematics, programming, and financial theory, and may include bonuses and profit-sharing components.

What is a Quantitative Modeling job?

A Quantitative Modeling job involves using mathematical, statistical, and computational techniques to analyze data and construct models that help businesses make informed decisions. Professionals in this field work in finance, risk management, economics, and other industries to develop predictive models, optimize strategies, and assess uncertainties. They often use programming languages like Python, R, or MATLAB, along with machine learning and statistical methods, to solve complex problems.

What are the key skills and qualifications needed to thrive in the Quantitative Modeling position, and why are they important?

To excel in Quantitative Modeling, a strong foundation in mathematics, statistics, and data analysis is essential, often complemented by a degree in a quantitative field such as mathematics, finance, engineering, or physics. Proficiency in programming languages like Python, R, MATLAB, or statistical software, as well as familiarity with data visualization tools and financial modeling certifications (such as CFA or FRM), is highly valued. Effective quantitative modelers possess strong problem-solving abilities, attention to detail, and the ability to communicate complex findings clearly to both technical and non-technical stakeholders. These skills enable accurate, data-driven decision-making and the creation of robust predictive models in business, finance, or technology sectors.

What are the most commonly searched types of Quantitative Modeling jobs in Houston, TX? The most popular types of Quantitative Modeling jobs in Houston, TX are:
What are popular job titles related to Quantitative Modeling jobs in Houston, TX? For Quantitative Modeling jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Quantitative Modeling jobs in Houston, TX look for? The top searched job categories for Quantitative Modeling jobs in Houston, TX are:
What cities near Houston, TX are hiring for Quantitative Modeling jobs? Cities near Houston, TX with the most Quantitative Modeling job openings:
Quantitative Modeling jobs near you
Infographic showing various Quantitative Modeling job openings in Houston, TX as of July 2026, with employment types broken down into 70% Full Time, 12% Part Time, and 18% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $162,086 per year, or $77.9 per hour.

Quantitative Risk Manager

Expand Energy

Spring, TX • On-site

Full-time

Re-posted 14 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.

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