Requirements:

📍Over 5 years of experience in high-frequency trading (HFT) firms. 📍Deep expertise in applying machine learning (ML) models to HFT strategies. 📍Practical experience with ML pipelines operating across multiple exchanges, both independently and collectively. 📍Demonstrated success in developing sophisticated statistical arbitrage strategies that capitalize on price discrepancies between multiple instruments. 📍Eagerness to expand knowledge in high-frequency trading and implement it across numerous exchanges. 📍Competence in overseeing the entire pipeline: from data sampling and feature creation to strategy deployment in production. 📍Proficiency in at least one programming language, with a preference for Python - C++ is very advantageous. 📍Confident, resilient, highly motivated, and proactive demeanor. 📍Ability to work effectively with colleagues from diverse backgrounds and a strong willingness to learn.

Bonus:

📍Experience in mentoring, managing people, and leading interns or a team of researchers.

Key Responsibilities:

📍Develop and implement statistical arbitrage strategies using ML techniques. 📍Investigate new trading ideas by analyzing market data. 📍Design features and models to predict the behavior of hundreds to thousands of securities within a 10-second to 10-minute timeframe, across various underlying assets. 📍Collaborate with ML pipelines to support the strategy development process. 📍Continuously optimize and improve existing models. 📍Communicate efficiently with internal teams. 📍Mentor and potentially lead team members.