Quantitative Researcher Intern

About the role

You’ll learn the scientific craft behind systematic trading, working with senior researchers to take ideas from hypothesis through rigorous backtesting to production — mining large-scale market data for predictive signals and structural inefficiencies.

About the internship

Duration: 3–6 months (flexible start; full-time preferred)
Location: Remote, or our Singapore or New York office
Who it’s for: Students and early-career researchers with a strong quantitative background and a scientific mindset.

What you’ll do

• Research and backtest trading signals using statistical and machine-learning techniques.
• Clean, transform, and analyse large market datasets to surface predictive features.
• Investigate market microstructure and exchange dynamics with rigour and honesty.
• Contribute to portfolio construction and execution research aimed at better risk-adjusted returns.
• Document findings clearly and present them to traders and fellow researchers.
• Pair with developers and traders to deploy validated research into live systems.

What you bring

• Pursuing or recently completed a degree in a quantitative field (Mathematics, Physics, Statistics, Computer Science, or related).
• Solid programming skills in Python (PyTorch, TensorFlow, or scikit-learn a plus).
• A strong grasp of probability, statistics, and time-series analysis.
• Creativity, scientific rigour, and comfort with ambiguity and large datasets.
• Self-direction and a genuine enthusiasm for research.
• Fluency in English is required.

What you’ll get

• Access to proprietary datasets and strong computing infrastructure.
• Mentorship from researchers with deep experience in quantitative finance.
• Competitive, performance-linked compensation.
• A collaborative research culture built on innovation and intellectual honesty.
• A clear path to a full-time role for strong performers.
• Flexibility to work remotely or from our Singapore or New York office.