Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International; Greater London; On-site; GBP 16,000 - 21,000; Full time

Job summary

Castleton Commodities International (CCI) in London is offering a Data Science & Technology Internship focused on time series forecasting for energy market data. You will work with our Global Data Science team to analyze market fundamentals in Power, Natural Gas and Oil, and help forecast price movements to support risk management decisions.

The role emphasizes collaboration with traders and data scientists, development of ML models, and data ingestion workflows as part of a cutting-edge data

Qualifications

• Pursuing or holding a Bachelor's degree in Mathematics, Statistics, Physics, CS or related field with ML focus.
• Expected graduation Winter 2027 or Spring/Summer 2028.
• Experience applying ML techniques to time series data and market dynamics.
• Strong Python programming skills (Pandas/NumPy).

Responsibilities

• Analyze time series data related to market fundamentals in Power, Natural Gas and Oil sectors.
• Develop and optimize ML models for time series forecasting (ARIMA/SARIMA, XGBoost, LSTM).
• Assist in end-to-end data ingestion and data flow to investing teams.
• Collaborate with Data Scientists, Analysts and Traders to understand data architecture and requirements.

Skills

Python

Time series forecasting

ML techniques

Communication skills

Analytical skills

Education

Bachelor's degree in Mathematics/Statistics/CS

Tools

Pandas

NumPy

ARIMA/SARIMA

XGBoost

LSTM

Job description

Application Deadline: September 1, 2026 at 11:59 pm EST

Program Summary - Data Science & Technology Internship

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 a motivated and detail-oriented Machine Learning Intern with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in our London office. 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.