Quantitative Researcher (AI)

TL;DR

Quantitative Researcher (AI): Developing predictive features and research pipelines for machine learning models, focusing on cash equities, futures, and other liquid asset classes with an accent on high-frequency market data and unstructured alternative datasets. Focus on tree-based models, deep learning, NLP/LLM, and deploying signals into production.

Location: Hong Kong

Company

Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors.

What you will do

• Engineer predictive features from high-frequency market data and unstructured alternative datasets for machine learning (ML) models.
• Develop research pipelines on a distributed compute cluster for tree-based models, deep learning, NLP/LLM, and related ML models.
• Design and prototype ML-driven alphas for cash equities, futures, and other liquid asset classes.
• Collaborate with researchers and developers to deploy signals into production, and perform iterative improvements based on real performance.
• Track academic and industry advances in machine learning and present actionable ideas to the team.

Requirements

• MS or PhD in computer science, statistics, mathematics, or a related quantitative discipline from a top-tier university.
• Minimum 5 years of alpha-research experience at a leading buy-side firm or global bank.
• Expertise in tree-based models, deep learning, and NLP/LLM with strong understanding of probability and overfitting-control practices.
• Proficiency in python (and preferably C++ or similar), coupled with experience on distributed/hybrid compute environments.
• Excellent analytical, verbal, and written communication skills, with a proactive, ownership-driven mindset suited to the fast-paced trading floor.

Culture & Benefits

• Foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals.
• Teamwork-oriented and collaborative environment that encourages ideas—at all levels—to be shared.
• Provide learning and educational offerings and opportunities to make an impact.
• Encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.