Data Science Machine Learning Internship (Summer 2027)

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. Its strategically integrated platform has generated strong risk-adjusted returns for investors since the company’s 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 its investment strategy. The company is seeking a motivated, detail-oriented Machine Learning Intern with a strong interest in quantitative analysis, particularly time series forecasting, to join the Global Data Science team in the London office.

This internship provides an opportunity to work with fundamental market data to generate insights that support the company’s commercial trading business. You will analyze time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors to help identify key supply and demand drivers. These insights will support forecasting price movements and 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 to ensure 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.
• Identify and back-test 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 a related technical field, with a focus on 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.