About EG

Engineers Gate (EG) is a leading investment manager founded in 2014 as a quantitative, computer-driven trading firm. Today, EG operates as a diversified, multi-strategy investment platform that combines systematic research with selective discretionary approaches.

EG's multi-manager platform allows independent investment teams to pursue distinct strategies while benefiting from shared infrastructure, risk management, and operational support. The firm’s collaborative groups of researchers, engineers, and investment professionals deploy sophisticated statistical models, proprietary technology, and a centralized data platform to isolate and solve challenging problem sets in the global financial markets.   

About The Role

We are seeking a motivated Quantitative Researcher to join one of our systematic equity trading teams. In this role, you will leverage the team’s existing research and trading infrastructure to research, develop, and support systematic equity strategies across the full trading lifecycle, from alpha research and signal generation to portfolio construction, execution, and ongoing risk management.

The ideal candidate has a strong quantitative foundation, hands-on experience with systematic equity strategies, and an interest in translating research into live trading. This individual will work closely with the Portfolio Manager within a collaborative, fast-paced environment.

Key Responsibilities

• Clean, validate, and analyze large-scale raw datasets to build a reliable foundation for US and China equities alpha research
• Assist Portfolio Managers in developing tools to analyze, optimize, and monitor portfolio performance
• Apply statistical and machine learning techniques, including deep learning models where appropriate, to enhance signal generation and forecasting
• Contribute across the full trading lifecycle: ideation, research, backtesting, optimization, deployment, and live performance monitoring
• Stay informed on equity market structure, short-horizon dynamics, emerging data sources, and relevant technological advancements across both US and China markets

Qualifications

• MS or PhD in a quantitative field (e.g., mathematics, statistics, computer science, physics, engineering) is a plus.
• 1–5 years of experience in systematic equity research or quantitative trading.
• Strong quantitative, mathematical, and programming skills; Python required
• Working knowledge and practical experience applying machine learning models; experience with deep learning is a plus.
• Familiarity with China equity markets or cross-border trading dynamics is a plus