Junior Quantitative Researcher (Machine Learning)

Job Description

Geneva Trading is seeking a Junior Quantitative Researcher to join their global quantitative trading team in Dublin. The candidate will be responsible for researching, developing, and deploying automated intraday and mid-frequency trading strategies using machine learning models and advanced quantitative methods. This role requires a blend of quantitative research and software engineering skills, with a focus on applying statistical techniques to drive real-time trading decisions.

The Junior Quantitative Researcher will work within a lean, skilled team, contributing to all stages of the pipeline, from data preprocessing to model deployment. They will also enhance research and trading infrastructure through machine learning methods, ensuring the seamless integration of research and real-time execution.

Role Involves:

• Designing and executing research experiments to develop innovative models and strategies.
• Developing production-ready code for live trading integration.
• Enhancing research and trading infrastructure through machine learning methods.
• Monitoring live trading strategies for performance issues.
• Integrating external libraries into production code.
• Optimizing model training and backtesting using parallel, distributed, and cloud computing.
• Exploring opportunities for strategy expansion across global futures products.
• Staying current with industry advancements.

Requirements:

• Master’s or PhD in a STEM field (e.g., Machine Learning, Computer Science, Physics).
• 1+ years of applied machine learning experience in a commercial or academic setting, or 1+ years in quantitative research or development in trading.
• Strong understanding of multivariate statistics, time-series analysis, machine learning, and optimization.
• Strong programming skills in Python, including libraries like NumPy, Pandas, and Scikit-learn.
• Familiarity with Q/KDB and Git.
• Strong mathematical ability in linear algebra and calculus.