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Engineers Gate (EG) is a leading quantitative investment company focused on computer-driven trading in global financial markets. We are a team of researchers engineers and financial industry professionals using sophisticated statistical models to analyze data and identify predictive signals to generate superior investment returns. EGs investment teams each focus on their independent strategies while utilizing the firms proprietary state-of-the-art technology and data platform to optimize their alpha research.
We are seeking a highly motivatedQuantitative Research Intern to join one of our investment this hands-on research role you will collaborate with experienced team members to explore data develop predictive models and support research initiatives. This opportunity provides practical experience applying quantitative skills in a dynamic real-world environment.
We value continuous learning and development and this role offers the chance to work closely with professionals across research engineering and investment teams. If you thrive in a fast-paced data-driven setting we encourage you to apply.
Conduct research on large and complex datasets to identify trends patterns or predictive signals
Assist in designing testing and evaluating quantitative models or strategies
Support feature engineering data analysis and model validation
Analyze results and contribute to recommendations for research or strategy development
Communicate research findings clearly to team members
Currently pursuing an undergraduate or graduate degree in a quantitative field (Computer Science Mathematics Engineering Physics etc.)
Strong programming skills in Python and SQL
Experience or coursework in quantitative research data analysis or modeling
Comfortable working with large datasets and applying statistical or machine learning techniques
Strong analytical thinking creativity and attention to detail
Excellent written and verbal communication skills
High ownership curiosity and a growth mindset
Ability to thrive in a fast-paced and collaborative environment
Required Experience:
Intern
Intern