Castleton Commodities International is a leading commodity trading and investment firm. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, data and technology skills, and industry knowledge to invest in, and develop select commodity infrastructure assets. CCI focuses its activities on the markets it understands best, while constantly striving to expand its knowledge base and network of relationships in order to participate in new markets.
CCI continues to build out a best-in-class data science platform which supports data access, management and analytics via ml platforms, visualization tools, reporting, APIs, and associated toolkits to promote a robust analytics framework which is vital to its investment process. This role will have significant exposure to commercial investment teams in the Firm.
- Assist with data architecture and data management projects for both new and existing data sources
- Help transition existing data sets, databases, and code to a new technology stack
- Build an end to end data ingestion process and publishing to investing teams
- Involved in the assessment of data loads for tactical errors and build out appropriate workflows, as well as create data quality analysis that identifies larger issues in data
- Liaise with commercial investment teams in order to gain understanding of current data flow, data architecture, investment process as well as gather functional requirements
- Assess gaps in current datasets and remediate
- Pursuing a Bachelor’s or higher degree in Computer Science, Management Information Systems, or related field of study.
- Strong analytical skillset with demonstrated attention to detail.
- Passion for data (both big and small) and data analytics
- Intermediate experience in Python/Java and SQL.
- Interest and passion for technology – programming, cloud-based technologies, and analytics.
- Ability to communicate and interact with a wide range of users ranging from very technical to non-technical.
- Strong analytics skills with demonstrated attention to details.