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 & Skills:
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
