We are looking for a highly motivated Quantitative Researcher Intern to build and maintain predictive models that analyze and forecast price movements from financial data. You will also contribute to developing data-driven trading strategies using different methods: machine learning (ML),deep learning (DL),...

Key Responsibilities

Support to design and implement predictive models for financial time series

Develop and backtest trading strategies using technical indicators and ML/DL

Optimize model performance (feature engineering, hyperparameter tuning, evaluation)

Deploy and maintain ML/DL pipelines in production

Work with engineers to integrate models into live systems

Monitor and improve strategy performance based on market changes

Keep up with the latest in quantitative finance and AI

Proficient in Python, with strong analytical thinking and problem-solving skills

Solid foundation in mathematics, statistics, and probability, including:Linear Algebra, Calculus, Probability, Statistics, and Optimization

Familiar with core machine learning techniques: Regression, classification, model evaluation, ensemble methods.

Basic knowledge of deep learning, with hands-on experience using PyTorch

Experience working with time series data, including preprocessing and modeling

Experience in backtesting and evaluating trading strategies

Good understanding of technical analysis and financial market

Nice to Have:

Knowledge of portfolio optimization, risk management, or market microstructure

Experience with cloud deployment or real-time pipelines