ML Researcher / Quant Researcher

We are looking for an ML Researcher with a strong mathematical background and research mindset.

We need a specialist who can not only train models but also find patterns in data, test hypotheses, and distinguish real results from random ones.

What you will be doing

• Researching financial time series and market data.
• Developing ML models for forecasting and discovering trading signals.
• Formulating and testing hypotheses.
• Performing backtesting and walk-forward validation.
• Preventing data leakage, look-ahead bias, and overfitting.
• Evaluating model robustness on new data.

What is important

• Strong foundation in mathematics, probability theory, and statistics.
• Knowledge of ML: linear models, boosting, basics of Deep Learning.
• Python, NumPy, pandas, scikit-learn, CatBoost / LightGBM.
• Ability to conduct research independently and critically evaluate results.

Candidates with one of the following advantages are especially interesting

1. Strong education: MIPT, HSE (Faculty of Computer Science, Faculty of Mathematics), MSU (VMK, MechMat), SPbSU (Math-Mech), SHAD.

2. Achievements in competitions: Kaggle, Codeforces, ICPC, mathematics and algorithmic olympiads.

3. Quant Research / HFT experience: developing trading strategies, working with market data, searching for signals, and backtesting.

Meeting at least one of these criteria is sufficient.

Will be a plus

PyTorch, SQL, Docker, MLflow, C++ / Rust, research publications, and personal ML projects.

Experience in algorithmic trading is not required. We also consider strong students and junior researchers.

Conditions

• Fully remote work, full-time.
• Interesting research tasks.
• Minimal bureaucracy.
• Salary is discussed individually, no strict range.
• Payments in USDT weekly.