Job description

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 s eeking 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.

Requirements

Must-haves

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
Academic background in Mathematics, Physics, Computer Science, Engineering or a related field
A history of continuous and self-directed learning
2-5 years of working experience in quantitative research in equities/futures
Excellent attention to detail, strong written/verbal communication

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpython

Platform: greenhouse
Effort: quick