Search the 12 jobs at Castleton Commodities International

Technology Project Manager responsible for overseeing and coordinating multiple projects in the Global Data Science & Technology business. Requires project management skills, software development understanding, and communication with technical and non-technical stakeholders. Responsibilities include project oversight, planning, progress monitoring, stakeholder communication, and risk management. Qualifications include a Bachelor's degree and 5 years of project management experience focusing on technology projects.

The LNG Scheduler at Castleton Commodities International will manage the logistics for LNG cargo operations, evaluate trading opportunities, oversee cargo operations, and ensure compliance with regulations. This role requires strong analytical skills, the ability to work in a trading environment, and interaction with various stakeholders.

The Associate will conduct in-depth analysis of the European energy market, specifically the EU power market, providing research support to trading operations. Responsibilities include developing fundamental supply and pricing models, monitoring market trends, and assisting traders in identifying opportunities.

As an Associate Systems Integration Developer, you will enhance and integrate enterprise systems, ensuring data flow and consistency. You will design, develop, and maintain integration solutions while collaborating with stakeholders. Responsibilities include troubleshooting integration issues and documenting processes, leveraging your experience in cloud and enterprise systems integration.

The Data Scientist will advance the data science capabilities by performing time series forecasting and machine learning model building in the global oil markets. Responsibilities include delivering end-to-end solutions, mentoring junior data scientists, and providing insights to commercial teams while analyzing oil and shipping market fundamentals.

The Front Office Software Engineer will develop, support, and maintain investment, trading, and analytics platforms while collaborating with commercial trading teams and the Data Science team to enhance trading processes and create analytics tools. The role emphasizes cloud-first development and modern software engineering practices.

The Data Engineer will implement data management platforms, create data ingestion pipelines, and manage data architecture projects. They will lead data analysis using machine learning, manage end-to-end data processes, ensure data quality, and assist commercial teams with data architecture understanding and functional requirements.

As a Weather Data Scientist at CCI, you will enhance weather forecasting models, conduct research, and manage the ingestion and analysis of vast weather data sets. Your role involves applying machine learning and time series analysis to improve model accuracy and provide valuable insights into weather patterns.

The EMA Scheduler will manage daily energy management activities, including the scheduling of generating units, liaising with internal and external stakeholders, and engaging in business development. Responsibilities include participating in off-hours coverage and maintaining adherence to ISO regulations.

The P&L Analyst role involves timely and accurate P&L reporting, monitoring trading positions, analyzing market price indicators, and performing daily reconciliations in a risk control function. The analyst supports traders and resolves discrepancies in P&L estimates, validating marks against third-party sources, and providing guidance on modeling transactions.

The role involves performing in-depth analysis of the US power and renewable energy markets, developing and improving supply and demand models, pricing models, and communicating findings to support trading activities. The analyst will collaborate with traders and other analysts to identify market opportunities and contribute to analytical tools.

The role involves executing data architecture and management projects, transitioning existing data sets to new technologies, leading data analysis using machine learning, managing data ingestion processes, and improving data quality and vendor management, all while collaborating with commercial teams to understand data flow and investment processes.