Strong fit for candidates with a technical background in quantitative methods who can manage research projects end-to-end, and who are experienced in equities/futures trading.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Engineers Gate via Greenhouse
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, detail-oriented Quantitative Researcher to join a small, highly collaborative team managing a global, mid-frequency statistical arbitrage portfolio. The researcher will contribute across the full research lifecycle, from exploring alternative datasets and developing trading signals to enhancing portfolio construction, risk, and transaction cost models and implementing research in production.
The team places a premium on ideas motivated by an understanding of underlying economic mechanisms, combining this perspective with advanced statistical and machine learning techniques.
Key Responsibilities:
Explore unique alternative datasets in order to develop novel trading signals
Develop and enhance frameworks for portfolio construction
Utilize state of the art machine learning and data science techniques to improve stock level insights
Enhance the team's array of risk and transaction cost models
Write robust and production quality code
Manage the full pipeline of research projects from idea generation to implementation
Qualifications:
Academic background in Mathematics, Physics, Computer Science, Engineering or a related field
A history of continuous and self-directed learning
Strong mathematical and modeling skills (proficiency in optimization theory is preferred)
Proficiency in coding (Python, C++ preferred)
Master's or PhD in any quantitative field is a plus, but not required.
2-5 years of working experience in quantitative research in equities/futures
Excellent attention to detail, strong written/verbal communication
The base salary for this role is anticipated to be $130,000–$200,000, excluding potential bonuses, additional comp compensation, and benefits. Actual compensation will depend on various factors including skills, experience, and qualifications.