Academic background in Mathematics, Physics, Computer Science, Engineering, or a related field
History of continuous and self-directed learning
Strong mathematical and modeling skills, with a preference for optimization theory
Proficiency in coding, particularly in Python and C++
2-5 years of experience in quantitative research in equities or futures
Excellent attention to detail and strong communication skills
Responsibilities
Explore unique alternative datasets to develop novel trading signals
Develop and enhance frameworks for portfolio construction
Utilize advanced machine learning and data science techniques for stock-level insights
Enhance risk and transaction cost models
Write robust, production-quality code
Manage the full pipeline of research projects from idea generation to implementation
Benefits
Collaborative team environment
Opportunity to work on a global, mid-frequency statistical arbitrage portfolio
Focus on innovative ideas driven by economic understanding
Access to advanced statistical and machine learning techniques
Potential for professional growth and continuous learning
Full Job Description
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.
About Engineers Gate
Engineers Gate is a quantitative investment management firm that was founded in 2014 by Greg Baxter, a former head of research at Point72 Asset Management. The firm uses a data-driven approach to investing and focuses on generating alpha through systematic trading strategies. Engineers Gate manages several funds, including the Engineers Gate Alpha Fund, which has consistently outperformed the S&P 500 since its inception. The firm is headquartered in New York City and has a team of experienced professionals with backgrounds in finance, mathematics, and computer science.
