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Internship Energy Quant Jobs (NOW HIRING)

ConocoPhillips

Intern, Trading Analytics 2027

Houston, TX · On-site

$14.25 - $19/hr

... quants, and traders on live commercial projects. Interns will be paired with a supervisor, mentor ... Interest in energy or commodity markets (crude oil, natural gas, NGLs, power, or LNG) * Genuine ...

Fervo Energy

Electrical Power Engineer

Houston, TX · On-site

... energy integration. Working closely with internal engineering teams, consultants, vendors, and ... Internship, consulting, utility, or industry experience related to electrical power systems

Trading Interview

$213 - $288/hr

... internship * Meaningful projects: Each project, advised by a trader, promotes a comprehensive ... Energy across all major global markets. We have also leveraged our expertise and technology to ...

DRW

Quantitative Trading Analyst Intern

Chicago, IL · On-site

$250K/yr

... internship * Meaningful projects: Each project, advised by a trader, promotes a comprehensive ... Energy across all major global markets. We have also leveraged our expertise and technology to ...

P2P

Quantitative Trading Analyst Intern

Chicago, IL · On-site

$240 - $260/hr

... internship * Meaningful projects: Each project, advised by a trader, promotes a comprehensive ... Energy across all major global markets. We have also leveraged our expertise and technology to ...

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Internship Energy Quant information

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$2.4K

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$7.7K

How much do internship energy quant jobs pay per month?

As of Aug 23, 2026, the average monthly pay for internship energy quant in the United States is $5,290.17, according to ZipRecruiter salary data. Most workers in this role earn between $3,000.00 and $7,500.00 per month, depending on experience, location, and employer.

What is an Energy Quant internship?

An Energy Quant internship is a temporary position where students or recent graduates work with quantitative teams in the energy sector. Interns typically use mathematical models, statistical techniques, and programming skills to analyze energy markets, forecast prices, and support trading strategies. This role provides hands-on experience with real-world data, exposure to financial modeling, and insight into how quantitative analysis drives decisions in the energy industry. It's a valuable opportunity for those interested in combining finance, mathematics, and the energy sector.

What do Energy Quant interns do?

As an Energy Quant Intern, you can expect to work on projects involving data analysis, model development, and risk assessment related to energy markets. Typical tasks may include gathering and cleaning large datasets, assisting with building or refining quantitative models for price forecasting, and supporting senior quants in research or reporting. You'll likely collaborate with traders, analysts, and other quantitative team members, providing valuable insights that inform trading strategies and risk management. This hands-on experience not only deepens your technical skills but also helps you understand the practical challenges of applying quantitative methods in fast-paced, real-world energy markets.

What skills and qualifications are needed to thrive as an Energy Quant intern?

To thrive as an Internship Energy Quant, you need strong quantitative skills, a background in mathematics, finance, engineering, or physics, and proficiency in data analysis. Familiarity with programming languages like Python or R, experience with statistical modeling tools, and knowledge of energy markets are commonly expected. Analytical thinking, attention to detail, and effective communication skills help interns interpret complex data and convey insights to diverse teams. These skills and qualities are crucial for accurate market analysis, risk assessment, and supporting data-driven decision-making in the dynamic energy sector.

What is the difference between Internship Energy Quant vs Energy Analyst?

AspectInternship Energy QuantEnergy Analyst
Required CredentialsCurrently pursuing or recent graduate in finance, economics, or related fieldsBachelor's or master's in energy, economics, or related fields
Work EnvironmentInternship programs, often in finance or energy firmsFull-time roles in energy companies, consulting firms, or utilities
Employer & Industry UsageUsed as entry-level training positions in energy finance and tradingRegular professional roles analyzing energy markets and operations

The main difference is that an Internship Energy Quant is a temporary, entry-level position focused on gaining experience in energy finance and quantitative analysis, often during studies. An Energy Analyst is a full-time professional role responsible for analyzing energy markets, forecasting, and supporting decision-making within energy companies or consultancies.

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Internship Energy Quant jobs near you
Infographic showing various Internship Energy Quant job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, 19% Part Time, and 1% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $63,482 per year, or $30.5 per hour.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Stamford, CT

Full-time

Re-posted 2 days ago

Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

Apply