Quantitative Research Intern

You will be working as a Quantitative Research Intern where you will focus on designing, testing, and refining systematic strategies across global markets. Your responsibilities will include: - Collecting, cleaning, and analyzing time-series data from financial markets - Identifying and testing quantitative signals such as momentum, mean-reversion, spreads, etc. - Building backtesting frameworks and performance dashboards in Python - Applying statistical techniques to validate and optimize strategies - Presenting findings with clear data visualizations and concise documentation To excel in this role, you should have a strong understanding of statistics, probability, and time-series analysis. Proficiency in Python libraries such as NumPy, Pandas, statsmodels, scikit-learn, and matplotlib is essential. You should also possess the ability to structure research from raw data to actionable insight, along with an analytical mindset, curiosity, intellectual aptitude, and learning agility. In addition to the above responsibilities and qualifications, you will have the opportunity to benefit from direct mentorship, exposure to multi-asset data, and systematic research workflows. You will also have the chance to turn your work into real, deployable strategies. You will be working as a Quantitative Research Intern where you will focus on designing, testing, and refining systematic strategies across global markets. Your responsibilities will include: - Collecting, cleaning, and analyzing time-series data from financial markets - Identifying and testing quantitative signals such as momentum, mean-reversion, spreads, etc. - Building backtesting frameworks and performance dashboards in Python - Applying statistical techniques to validate and optimize strategies - Presenting findings with clear data visualizations and concise documentation To excel in this role, you should have a strong understanding of statistics, probability, and time-series analysis. Proficiency in Python libraries such as NumPy, Pandas, statsmodels, scikit-learn, and matplotlib is essential. You should also possess the ability to structure research from raw data to actionable insight, along with an analytical mindset, curiosity, intellectual aptitude, and learning agility. In addition to the above responsibilities and qualifications, you will have the opportunity to benefit from direct mentorship, exposure to multi-asset data, and systematic research workflows. You will also have the chance to turn your work into real, deployable strategies.