Engineers Gate

investment manager

QuantitativeResearchIntern

Hong Kong
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Entry candidates.

The Brief

“Quantitative Research Intern at Engineers Gate. Skills: quantitative research, data analysis, statistical modeling, machine learning. Clean, validate, and analyze diverse datasets to provide a reliable foundation for global equities alpha research. Develop alpha factors with economic insights and statistical significance from multi-dimensional data”

What You'll Achieve.

contributing to work that has a tangible impact on how we invest

Industry & Context.

investment manager
Problems you'll solve

analytical thinking; isolating and solving challenging problem sets in the global financial markets

What They're Looking For.

Must Have

Bachelor’s, Master’s, or Ph. D. from a top-tier university in a quantitative field (Computer Science, Mathematics, Engineering, Physics, Statistics, Finance, Economics, or related), programming skills in Python (required), experience with SQL, experience with databases, experience with Linux environments, Experience or coursework in quantitative research, Experience or coursework in data analysis, Experience or coursework in statistical modeling, Experience or coursework in machine learning, Comfortable working with large datasets, applying statistical or machine learning techniques to financial data

Nice to Have

PhD preferred

What You'll Do.

and analyze diverse datasets to provide a reliable foundation for global equities alpha research

Develop alpha factors with economic insights and statistical significance from multi-dimensional data

Design rigorous backtesting frameworks for performance evaluation and robustness testing

and evaluating quantitative models and strategies

Communicate research findings clearly to team members

How You'll Work.

Team & Collaboration

working directly alongside experienced researchers and engineers; collaborative environment; Communicate research findings clearly to team members

Communication Scope

Excellent written and verbal communication skills

Full 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're looking for intellectually curious, driven students at both the undergraduate and graduate level to join one of our investment teams as a Quantitative Research Intern. This is a hands-on research role where you'll be working directly alongside experienced researchers and engineers, digging into real data, asking meaningful questions, and contributing to work that has a tangible impact on how we invest. Whether you're drawn to statistical modeling, machine learning, or the challenge of finding signal in noisy financial data, this internship is a chance to apply and sharpen your skills in a rigorous, collaborative environment. Key Responsibilities Clean, validate, and analyze diverse datasets to provide a reliable foundation for global equities alpha research Develop alpha factors with economic insights and statistical significance from multi-dimensional data Design rigorous backtesting frameworks for performance evaluation and robustness testing Assist in designing, testing, and evaluating quantitative models and strategies Communicate research findings clearly to team members Qualifications Bachelor’s, Master’s, or Ph. D. from a top-tier university in a quantitative field (Computer Science, Mathematics, Engineering, Physics, Statistics, Fina

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