Senior Quant Research

Role Summary
Lead the development and refinement of quantitative trading strategies leveraging advanced statistical and machine learning techniques. Drive research initiatives to generate alpha and optimize portfolio performance within a fast-paced, data-driven environment.

Key Responsibilities

• Design, implement, and backtest systematic trading models across multiple asset classes.
• Analyze large, complex datasets to identify predictive signals and market inefficiencies.
• Collaborate with engineers and traders to deploy and monitor live trading algorithms ensuring robustness and risk controls.
• Innovate by incorporating new data sources and cutting-edge quantitative methods to improve strategy performance.
• Mentor junior researchers and contribute to the continuous improvement of research processes and infrastructure.

Required Qualifications

• Advanced degree (MSc or PhD) in Mathematics, Statistics, Computer Science, Engineering, Physics, or related quantitative field.
• Minimum 5 years of experience in quantitative research, preferably within a Tier 1 quant or HFT environment.
• Strong proficiency in programming languages such as Python, C++, or R, with hands-on experience in data analysis and algorithmic model development.
• Deep knowledge of financial markets, derivatives, and quantitative finance concepts including time-series analysis and machine learning.
• Proven track record of developing profitable trading strategies and working effectively in collaborative, high-performance teams.

Application Instructions
Submit your resume and cover letter highlighting your quantitative research experience and relevant achievements to Tier 1 Quants recruitment portal.