Senior Quant Researcher

Responsibilities

• Design and deploy advanced ML and DL models for alpha signal generation across digital asset markets
• Work across the full model stack, including feature engineering, architecture selection, training, and validation
• Apply state-of-the-art techniques such as transformer architectures, graph neural networks, and reinforcement learning to financial prediction
• Build robust, production-grade research pipelines with a focus on preventing lookahead bias, data leakage, and overfitting
• Analyze microstructure, order flow, and cross-venue dynamics to improve signal quality
• Collaborate with engineers to transition models from research to production infrastructure
• Mentor junior researchers and maintain high standards of statistical rigor

Requirements

• PhD or equivalent research depth in Machine Learning, Statistics, Physics, Mathematics, or Computer Science
• Hands-on implementation experience with Transformers, GNNs, Reinforcement Learning, and boosting algorithms (XGBoost, LightGBM)
• Proven track record of applying ML in a live, capital-at-risk environment with measurable performance
• Exceptional programming skills in Python
• Deep understanding of ML failure modes in finance, including regime change and non-stationarity

Preferred Qualifications

• Knowledge of C++ or Rust for production performance
• Experience working with large, complex, or unconventional datasets, such as on-chain data
• Prior exposure to crypto markets and digital asset market structures

About the Company

AlgoQuant Asset Management is a multi-strategy digital asset manager allocating capital across 25+ internal and external quantitative trading pods. Founded in 2018, we have evolved into an institutional platform combining trading edge with strong governance and advanced technology, serving family offices and institutional investors globally.