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Engineers Gate is seeking a motivated Quantitative Researcher to join a small, collaborative team managing a global, mid-frequency statistical arbitrage portfolio.
You will explore alternative datasets, develop trading signals, and help improve portfolio construction, risk, and transaction cost models while delivering production-grade code.
Candidates typically have 2–5 years of experience in quantitative research, a strong mathematical background, and a degree in engineering, CS, or physics.
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.
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.
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.
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.