ML Quantitative Researcher

Salary: $6,000–$8,000 per month gross

What you will do

• Formulate and test hypotheses about market inefficiencies.
• Design predictive features using statistical transformations and learned representations.
• Analyze alternative data, time series, and nonlinear dependencies to identify market signals.
• Consider how model predictions can be integrated into trading strategies, including directional bets and spread convergence.
• Build reliable production data pipelines beyond notebook-based prototypes.

Requirements

• Deep understanding of machine learning concepts, model selection, and statistical reasoning.
• Hands-on experience with deep learning and gradient boosting frameworks, including a strong understanding of neural network internals.
• Ability to identify data leakage and prevent future information from contaminating financial backtests.
• Strong knowledge of statistics, probability theory, and stochastic processes.
• Strong Python skills; experience with pandas, Polars, or streaming data processing is beneficial.
• Professional English proficiency at B2 level or above.

Nice to have

• Graduate degree or background from SHAD or a similar top-tier technical or quantitative program.
• Competitive mathematics, physics, or computer science olympiad experience.
• Demonstrated performance in Kaggle or other machine learning competitions.

Culture & Benefits

• No prior finance experience is required; training covers market microstructure and portfolio construction.
• Work spans quantitative research and feature engineering.
• Emphasis is placed on honest evaluation of backtest results and understanding model assumptions, limitations, and failure modes.