Quantitative Researcher - 2027 Graduates

Graviton Research Capital is hiring a Quantitative Researcher to investigate market behavior and develop quantitative models and hypotheses for systematic trading. The role involves testing and validating signals, refining strategies, and working with technologists to bring research into production.

What you'll do:

• Discovering predictive patterns and sources of alpha from billions of market events
• Formulating hypotheses about market behaviour and designing experiments to test them
• Applying probability, statistics, optimization and machine learning to build predictive models and quantitative signals for systematic trading
• Designing robust backtests and statistical tests to distinguish genuine signals from noise
• Working with large and complex datasets to uncover patterns that aren't immediately visible
• Investigating market microstructure and how markets behave at different timescales
• Evaluating strategy performance, identifying weaknesses and continuously refining models
• Developing research infrastructure and AI-powered tools and agents that make experimentation faster and analysis deeper
• Working closely with technologists to translate research ideas into efficient, production-ready systems
• Exploring new techniques in machine learning, statistics and quantitative finance to uncover new sources of edge

What they're looking for:

• Degree in a quantitative discipline such as mathematics, physics, computer science, statistics, operations research or machine learning
• No active backlogs
• Strong programming skills in Python and/or C++
• Solid grounding in probability, statistics, linear algebra and optimization, with experience in machine learning, statistical modelling or data analysis, whether through coursework, research or personal projects
• Comfort working with large, complex datasets, and strong analytical thinking
• A passion for applying quantitative thinking and rigorous research to solve open-ended problems in markets
• Excellent communication skills, with the ability to explain complex ideas clearly
• Prior exposure to quantitative research, algorithmic trading, market microstructure, competitive mathematics or machine learning is valuable