What are the responsibilities and job description for the ML Quantitative Researcher position at Alexander Chapman?
We are partnering with one of the world’s leading hedge funds to hire a Machine Learning Quantitative Researcher to join their global systematic research team.
The successful candidate will be responsible for developing and enhancing machine learning models used in the generation of trading signals across multiple asset classes. You will conduct research on large-scale financial and alternative datasets, design and test predictive models, and contribute to the ongoing improvement of the firm’s systematic trading strategies.
Working closely with portfolio managers, engineers, and data scientists, you will help translate research ideas into robust, production-ready models. This includes feature engineering, model validation, performance analysis, and ensuring research outputs are rigorously tested under realistic market conditions.
The ideal candidate will have a strong background in machine learning, statistics, and probability, with excellent programming skills in Python. Experience applying ML techniques to time-series or financial data is highly desirable, along with the ability to work in a fast-paced, research-driven environment.