Junior Quantitative Researcher

2 weeks ago

Dublin, Dublin City, Ireland Geneva Trading Full time
**Quantitative Researcher (Machine Learning)**We are seeking a talented Quantitative Researcher to join our competitive global quantitative trading team at Geneva Trading. In this role, you'll research, develop, and deploy automated intraday and mid-frequency trading strategies using machine learning models and advanced quantitative methods. You'll work with large datasets, applying statistical techniques to drive real-time trading decisions.As part of a lean, skilled team, you will contribute across the entire pipeline, from data preprocessing to model deployment, ensuring the integration of research and real-time execution. This hands-on role combines quantitative research with software engineering, requiring strong coding abilities and the application of CI/CD, DevOps, and MLOps principles.**Key Responsibilities:*** Design and execute research experiments to develop innovative models and strategies, evaluating results rigorously.* Develop production-ready code for live trading integration, collaborating with developers.* Enhance research and trading infrastructure through machine learning methods, including data preprocessing, feature selection, model training, and backtesting.* Monitor live trading strategies for performance issues such as covariate shift.* Integrate external libraries into production code following best engineering practices.* Optimize model training and backtesting using parallel, distributed, and cloud computing.* Explore opportunities for strategy expansion across global futures products.* Stay current with industry advancements through research, competitions, and online communities.**Required Qualifications:*** **Academic Background**: Master's or PhD in a STEM field (e.g., Machine Learning, Computer Science, Physics).* **Experience**: 1+ years of applied machine learning experience in a commercial or academic setting, or 1+ years in quantitative research or development in trading.* **Skills**:+ 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.
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