Description

You will develop and optimize systematic trading strategies for US equities markets.

This role is remote.

Responsibilities

• Build and refine quantitative models for alpha generation and systematic trading.
• Design and execute realistic backtests, accounting for slippage, transaction costs, and market conditions.
• Engineer data pipelines to handle and process large datasets for model integration.
• Automate trading processes and end-to-end solutions using Python and SQL.
• Analyze backtest performance to tweak models for optimal execution in live environments.

Required Skills

• 4+ years of experience in quantitative research or similar roles.
• Proficiency in Python for data analysis, model development, and automation.
• Expertise in Python libraries including pandas, numpy, scikit-learn, and TensorFlow.
• Strong SQL skills for querying and manipulating large financial datasets.
• Experience with statistical modelling and alpha modelling.
• Hands-on experience with data engineering and building data pipelines.
• Deep understanding of backtesting, risk management, and strategy validation.
• Knowledge of mid-frequency and MFT trading strategies.
• Experience working with US markets and equities.

Key Skills

Education

Not specified