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 is building out a best in class data science platform as being on the forefront of data management and analytics is core to our investment platform. Overall, this position will be actively involved as the team executes on new data analysis (traditional and Machine Learning driven), creates new data ingestion pipelines, and sources new data sets. The role will assist with all aspects of data and will have significant exposure to our Risk and commercial investing teams in the Firm.
- Apply understanding of the mathematical/statistical fundamentals behind machine learning to improve existing applications and inspire new ones.
- Collaborate on machine learning models with other data scientists, analysts, traders, etc.
- Build end-to-end data ingestion processes and publish data to investing teams
- Work with desk heads, traders and analysts in order to gain understanding of current data flow, data architecture, investment process, and functional requirements for data science analysis
- Help drive alpha for users by assisting with identifying and back testing of new data sets
- Ad hoc research on project topics such as data and vendor trends, usage best practices, big data trends, artificial intelligence, vendors, etc.
- Pursuing a Bachelor’s or higher degree in Computer Science, Mathematics, Statistics, or related field of study with a focus in machine learning.
- 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.