Teams at Castleton Commodities International

Work with the Global Data Science team to analyze energy market time series, build and optimize forecasting models (ARIMA/SARIMA, XGBoost, LSTM), design data ingestion pipelines, back-test datasets, and deliver insights to traders and analysts to support forecasting and risk management.

Work with Data Science, Data Engineering, and Commercial teams to build and optimize data ingestion, ETL, and transformation pipelines using Python and SQL, publishing to Snowflake. Implement data quality checks, automate workflows (Airflow or similar), transition legacy datasets to cloud-native architectures, and document pipeline logic and data models for analytics and forecasting.

Summer internship contributing to front-office trading analytics: build Python microservices and APIs, develop real-time trading tools and visualizations (Streamlit), work with cloud-native AWS services, Kubernetes, Kafka and Snowflake, support CI/CD and DevOps, and help integrate ML-driven analytics into trading workflows.