Key Responsibilities · 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. Required Skills & Qualifications · 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.