Data Science Machine Learning Internship… at Castleton… · Stamford

Summary: Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. They are looking for motivated and detail-oriented Machine Learning Interns to join their Global Data Science team, focusing on analyzing time series data to support their commercial trading business. 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 Required 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 Required Skills: Machine Learning, Time Series Forecasting, ARIMA, SARIMA, Gradient Boosting, XGBoost, LSTM Networks, Linear Regression, Data Ingestion, Python, Pandas, NumPy Internship Start Date: Start in 2027 Summer