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Energy Quantitative Analyst Jobs (NOW HIRING)

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX · On-site

About us At ExxonMobil, our vision is to lead in energy innovations that advance modern living ... We are seeking a highly motivated quantitative analyst with strong valuation, structuring, and ...

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX · On-site

About us At ExxonMobil, our vision is to lead in energy innovations that advance modern living ... We are seeking a highly motivated quantitative analyst with strong valuation, structuring, and ...

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

... energy trading valuation and risk-control orientation. Job Duties & Responsibilities 1) ... Advanced Python skills for quantitative analytics, risk engines, data pipelines, and automated ...

Expand Energy

Quantitative Risk Analyst

Spring, TX

... energy trading valuation and risk-control orientation. Job Duties & Responsibilities 1) ... Advanced Python skills for quantitative analytics, risk engines, data pipelines, and automated ...

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Showing results 1-20

All JobsEnergy Quantitative Analyst Jobs

Energy Quantitative Analyst information

See salary details

$56.5K

$133.9K

$240K

How much do energy quantitative analyst jobs pay per year?

As of Jul 27, 2026, the average yearly pay for energy quantitative analyst in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

How much do energy quant analysts make?

Energy quantitative analysts typically earn between $70,000 and $150,000 annually, depending on experience, education, and location. Senior analysts or those with specialized skills in programming and data analysis can earn higher salaries, often exceeding $200,000 with bonuses and incentives.

What are Energy Quantitative Analysts?

Energy Quantitative Analysts are professionals who use mathematical models, data analysis, and statistical techniques to evaluate and predict trends in energy markets. They work with large data sets to assess prices, risks, and market behaviors related to commodities like oil, gas, and electricity. Their insights help companies make informed trading, investment, and risk management decisions. These analysts often work for energy companies, trading firms, or financial institutions with energy portfolios.

What is the difference between Energy Quantitative Analyst vs Energy Data Analyst?

AspectEnergy Quantitative AnalystEnergy Data Analyst
Required CredentialsDegree in finance, economics, or related field; proficiency in quantitative methodsDegree in data science, statistics, or related field; strong data analysis skills
Work EnvironmentFinancial firms, energy trading companies, or consulting firmsEnergy companies, utilities, or research organizations
Employer & Industry UsageFocuses on modeling, risk assessment, and trading strategiesFocuses on data collection, reporting, and operational insights

While both roles involve working with energy data, the Energy Quantitative Analyst primarily develops models for trading and risk management using advanced quantitative techniques. In contrast, the Energy Data Analyst focuses on analyzing energy data to support operational decisions and reporting. Both roles require strong analytical skills but differ in their core functions and industry applications.

Does JP Morgan hire quants?

JP Morgan hires quantitative analysts, often called quants, for roles in risk management, trading, and financial modeling. These positions typically require strong skills in mathematics, programming, and data analysis, and candidates often have advanced degrees in related fields. The firm is known for recruiting quants for its investment banking and asset management divisions.

What are the key skills and qualifications needed to thrive as an Energy Quantitative Analyst, and why are they important?

To thrive as an Energy Quantitative Analyst, you need a strong background in mathematics, statistics, and finance, typically supported by a degree in a quantitative field such as mathematics, engineering, or physics. Proficiency in programming languages like Python, R, or MATLAB, as well as experience with data analysis tools and energy market modeling systems, is essential. Exceptional analytical thinking, problem-solving skills, and effective communication set candidates apart in this role. These skills enable analysts to interpret complex market data, create accurate forecasts, and provide actionable insights for energy trading and risk management.

What types of data and analytical tools do Energy Quantitative Analysts typically use in their daily work?

Energy Quantitative Analysts frequently work with large datasets such as historical pricing, weather patterns, and energy consumption statistics. They utilize advanced analytical tools like Python, R, MATLAB, and specialized energy market software to build predictive models, analyze market trends, and assess risks. Collaboration with traders, risk managers, and data engineers is common, requiring strong communication skills to translate complex quantitative findings into actionable insights for decision-making. Familiarity with statistical modeling, time series analysis, and optimization techniques is essential to thrive in this dynamic environment.

What does an energy analyst do?

An energy analyst evaluates energy markets, prices, and consumption data to inform investment and operational decisions. They use statistical tools and modeling techniques to forecast trends and optimize energy resources, often working with data analysis software and industry regulations.

Are quantitative analysts in demand?

Quantitative analysts are in high demand across industries such as finance, energy, and technology due to their skills in data analysis, statistical modeling, and programming. The role often requires proficiency in tools like Python, R, or MATLAB, and demand is expected to grow with increasing reliance on data-driven decision making.
More about Energy Quantitative Analyst jobs
What cities are hiring for Energy Quantitative Analyst jobs? Cities with the most Energy Quantitative Analyst job openings:
What states have the most Energy Quantitative Analyst jobs? States with the most job openings for Energy Quantitative Analyst jobs include:
What job categories do people searching Energy Quantitative Analyst jobs look for? The top searched job categories for Energy Quantitative Analyst jobs are:
Energy Quantitative Analyst jobs near you
Infographic showing various Energy Quantitative Analyst job openings in the United States as of July 2026, with employment types broken down into 89% Full Time, 6% Part Time, 1% Temporary, and 4% Contract. Highlights an 83% Physical, 7% Hybrid, and 10% Remote job distribution, with an average salary of $133,877 per year, or $64.4 per hour.
Sr Energy Market Analyst (Engineering)

Sr Energy Market Analyst (Engineering)

NextEra Energy

Juno Beach, FL

Other

Posted 19 days ago

NextEra Energy rating

8.3

Company rating: 8.3 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

24th of 53 rated energy and utility

Job description

Requisition ID:  96128 

NextEra Analytics offers energy consulting services using industry-leading scientific analysis for planning, siting, forecasting and optimizing all forms of energy projects. Our optimization and analytics platforms integrate open-source technologies to leverage massive, diverse sets of utility operating data. This enables rapid development of operational solutions. Applying expertise in advanced mathematics, data and physical sciences, we solve some of the hardest problems facing the energy industry.
 

Position Specific Description

We are seeking a Senior Energy Quantitative Analyst to develop and optimize models for renewable energy generation, energy storage systems, and traditional utility assets. This role combines advanced quantitative analysis with power systems expertise to solve complex energy optimization problems. The analyst will develop mathematical models, perform quantitative studies of energy markets, and support trading, origination, and asset optimization decisions through sophisticated analytical tools and algorithms.

Key Responsibilities 

Perform pre-construction size optimizations for renewable generators (distributed/behind-the-meter and utility-scale), battery storage systems, and traditional generators

Develop and improve mathematical models and optimization algorithms using Python, R, and Excel

Optimize generator mix and sizing to serve electrical loads while meeting carbon reduction goals Work with trading and origination teams to interpret model valuations and respond to structured transaction requests

Design and construct risk management tools for evaluating company risk profiles and exposure levels

Review and provide feedback on technical documentation, software architecture, and project plans

Incorporate quantitative studies and analyses of spot/forward energy prices and volatilities for pricing, trading, and risk management into design optimization.

Possess knowledge of the principles involved in developing energy price forecasts, forward curves, and volatility models and apply these insights in making informed modeling decisions.

 

Preferred Qualifications 

Master's Degree in Engineering, Mathematics, Finance, Economics, or related quantitative field

2+ years of experience in quantitative analysis, energy markets, or related field

Advanced proficiency in Python and/or R programming with 2+ years of commercial software development experience

Strong mathematical and statistical modeling capabilities

 Power flow modeling experience or software development for power flow applications 

 Transmission planning and system analysis experience 

 Contingency analysis and power system reliability assessment skills 

Experience with distributed generation and behind-the-meter renewable solutions

Knowledge of utility tariff structures and integrated resource planning

Experience with energy market participation rules (Day-Ahead and Real-Time markets)

Proficiency with Python libraries: NumPy, Pandas, StatsModels, Matplotlib/Seaborn, Scikit-Learn, SciPy

Experience with code refactoring, OOP in Python/R, and package management

Unix/Linux and Windows development experience; AWS experience a plus

Web development, data visualization, or GUI development skills (RShiny, plotly, bokeh, Jupyter)

Knowledge of renewable energy and battery storage technologies

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