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About the Role
Seeking a Quantitative Research Intern for a systematic investment team focused on intraday US equities trading. You will own a research project from data exploration to model development and evaluation, working independently to develop hypotheses and build predictive models from time series data.
Responsibilities
- Clean, validate, and analyze financial time series datasets, including high-frequency data.
- Develop research hypotheses and build statistical or machine learning models to identify predictive signals for systematic trading.
- Design and run backtests to evaluate performance, robustness, and practical relevance, with careful attention to overfitting and data leakage.
- Refine models based on experimental results and feedback from portfolio managers.
- Communicate findings, assumptions, limitations, and proposed next steps clearly.
- Contribute original modeling ideas and explore promising research directions with the team.
Requirements
- Currently pursuing a Bachelor’s, Master’s, or Ph.D. in a quantitative field such as Computer Science, Mathematics, Engineering, Physics, Statistics, Finance, Economics, or a related discipline.
- Prior finance experience through an internship or full-time role, ideally in quantitative research.
- Academic research experience involving quantitative methods, such as a thesis, research assistantship, or substantial research project.
- Strong programming skills in Python.
- A solid foundation in probability, statistics, and time series analysis, with experience applying statistical modeling or machine learning to data.
- Ability to work independently and carry an open-ended research problem from initial exploration through model evaluation.
- Clear written and verbal communication.
Skills
- Python
- Statistical modeling
- Machine learning
- Time series analysis
Location
- US
Work Type
- Internship
Experience Level
- Intern
Education Level
- Bachelor's Degree
- Master's Degree
- Ph.D.
Salary/Compensations
- $100,000–130,000 (prorated for internship duration)
About the Company
- Engineers Gate (EG) is a leading investment manager founded in 2014 as a quantitative, computer-driven trading firm.
- 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.