Quantitative Research Intern

Required

• Currently enrolled in Columbia University's M.A. in Mathematics of Finance (MAFN) program, in good academic standing.
• Strong foundation in statistics, probability, quantitative methods, regression, and time-series analysis.
• Proficiency in Python and SQL, with an understanding of database structures, data processing, and coding best practices; comfort with Excel.
• Experience working with complex datasets and applying analytical or statistical methods to practical problems.
• Exceptional attention to detail, with a strong commitment to accuracy, analytical rigor, and quality of work.
• Genuine interest in financial markets, the broader economy, and applying quantitative analysis to a wide range of investment research questions
• Familiarity with Databricks, visualization platforms, machine learning, or AI-assisted analytical tools is a plus, but not required.
• Candidate Profile
• Intellectually curious, with strong analytical and problem-solving skills and an interest in applying quantitative methods to real investment questions.
• Self-motivated, organized, and capable of taking ownership of projects while managing multiple priorities.
• Strong written and verbal communication skills, with the ability to explain analytical findings clearly to investment professionals.
• Collaborative, adaptable, and eager to learn in a fast-paced investment research environment.