The Louis Dreyfus Company Internship Program 2025 is a six-month program that provides students an opportunity to gain hands-on experience in commodity trading industry. The program is designed to equip interns with foundational knowledge and professional skills in one of the company’s business platforms.
As a Data Scientist, Systematic Trading Intern, you will be introduced to and become an integral part of our Data Science, Systematic Trading team. You will work with experienced professionals in Data Science, Systematic Trading team and interact with colleagues to gain insight into the commodity industry. You will be given the opportunity to collaborate with various stakeholders to develop your own sense of the working environment in the business platform.
In your role, you will leverage your expertise in Python programming, ETL processes, and cloud-based DevOps to enhance our data infrastructure and software development practices used for trading. Your contributions will be key in supporting our systematic trading activities, and overall, our data-driven decision-making processes. Your work will allow us to empower our trading platforms with robust data solutions, crucial for developing and optimizing profitable trading algorithms. You will also face the exciting challenge of structuring complex and large financial time series data, ensuring our trading strategies are informed by accurate, high-quality data.
Internship duration:
- Between Jan to June 2025
Main Responsibilities:
- Review cutting-edge research papers on (Gen) AI to apply them to systematic trading activities
- Assist in the development and maintenance of ETL pipelines, focusing on the data requirements of our systematic trading projects
- Help manage complex financial time series data, like Futures contracts, to ensure the trading strategies are based on accurate data
- Support the creation of software solutions in Python, emphasizing scalability, performance, and reliability
- Contribute to automating and scheduling workflows to improve operational efficiency
- Collaborate with data scientists and trading teams, understanding their data needs and assisting in providing technical solutions for effective data analysis and strategy implementation
- Engage in code quality improvement through strong CI/CD practices, automated tests, and peer reviews
Requirements:
- Education: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Information Systems, Quantitative Finance, Engineering or a related field
- Technical Skills:
- Proficiency in Python for data manipulation, visualization, and dashboard development
- Familiarity with Scheduling Tools, and Machine Learning Operations principles and practices
- Willingness to learn software development best practices
- Knowledge of data cleaning techniques and best practices
- Interest in ETL processes, data modelling, warehousing
- Analytical Mindset:
- Ability to analyze complex data sets and derive meaningful insights
- Strong problem-solving skills
- Attention to detail
- Communication Skills:
- Excellent verbal and written communication skills
- Ability to explain technical concepts to non-technical stakeholders
- Other Skills & Knowledge:
- Willingness to work both independently and collaboratively in a team environment
- Interest and knowledge in economics, finance, systematic trading, or agricultural commodities sectors, is a plus
