Data Science Machine Learning Internship (Summer 2026)

Castleton Commodities International
London, England
13 months ago
Applications closed

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Machine Learning Engineer

Vermelo RPO M43Aq, United Kingdom
Posted
22 Jul 2025 (13 months ago)

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 2026 or Spring/Summer 2027.

  • 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.

Visit  https://www.cci.com/careers/life-at-cci/# to learn more!

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