Jobs at Castleton Commodities International

Design, build, and maintain end-to-end data ingestion pipelines and data architecture. Transition datasets to a new stack, map/standardize/normalize data, monitor data quality, manage vendor data inputs, and partner with commercial trading teams to gather requirements and support analytics and investing use cases.

Support building and optimizing data ingestion, ETL, and transformation pipelines using Python and SQL. Work with Snowflake and cloud platforms to store and validate structured and semi-structured data, automate workflows (Airflow), conduct data quality checks, and document pipeline architecture for use by trading and analytics teams.

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.

Summer internship on the Global Data Science team to develop and optimize time-series forecasting models (ARIMA/SARIMA, XGBoost, LSTM). Support end-to-end data ingestion, back-test datasets, collaborate with traders and analysts, and conduct ad hoc research on energy fundamentals and analytics trends.

Summer internship exposing students to physical and financial commodity trading, focusing on market analysis, risk, and technology. Tasks include building models, back-testing strategies, researching market fundamentals, identifying trading opportunities, and presenting findings. Participants receive mentorship, interact with senior leaders, and may be offered full-time roles or rotational analyst positions.

Two-year rotational graduate programme placing analysts on physical and financial commodity trading desks, risk, or weather teams. Responsibilities include market analysis, model development, statistical research, trade idea design and back-testing, and collaboration with internal and external research teams to manage trading risk.

The Hydrologist role involves designing and maintaining quantitative forecasting tools for hydrological variables, integrating them into power generation forecasts. The role requires strong programming skills and familiarity with hydrological modeling.

Negotiate and manage energy-commodity master agreements (ISDA, EFET, CPMA, transport/storage, emissions, FX), guarantees, and NDAs; maintain contract management records; liaise with counterparties and internal legal, credit, trading and operations teams; ensure correct legal/credit risk allocation and commercial controls; perform follow-up, recordkeeping and administrative tasks.

Work with traders and analysts to build scalable Python services and APIs, develop supply/demand models, market data analysis, real-time analytics, visualizations, and workflow automation for the front-office platform.

The Lead ETRM Solutions Architect is responsible for defining and evolving applications for commodities trading, ensuring scalable and resilient integration between various trading lifecycle components and overseeing architectural best practices.

Support day-to-day compliance operations for physical and financial commodities trading across Europe. Maintain and enhance monitoring dashboards, reports and data checks using Python, SQL, Power BI and Excel. Assist with regulatory analysis, audits, data requests and ad-hoc projects while collaborating with trading, operations, technology, risk and other stakeholders to enable compliant trading and investing activities.

The role involves developing and supporting applications for commodities trading, enhancing integrations, maintaining data pipelines, and collaborating with various teams for effective solution delivery.

Partner with stakeholders to discover AI use cases, configure enterprise GenAI tools, build and maintain high-quality prompts, contexts, and RAG/document-intelligence pipelines, evaluate and improve AI outputs, create reusable playbooks/templates, and enable teams on governed, production-ready AI workflows.