Quantitative Research Intern – Equity… at Jain Global · New York

Summary: Jain Global is an innovative multi-strategy investment firm seeking a highly motivated Quantitative Research Intern to join their Equity Arbitrage Equity Derivatives team. The role involves collaborating with portfolio managers and quantitative researchers to develop and refine models that identify pricing inefficiencies in equity markets, providing hands-on experience in statistical modeling and systematic trading. Responsibilities: - Analyze large-scale equity and market datasets to identify arbitrage opportunities and inefficiencies - Develop and implement quantitative models for equity arbitrage strategies (e.g., statistical arbitrage, factor-based relative value, pairs trading) - Conduct rigorous statistical testing, back testing, and validation of trading signals - Collaborate with researchers and developers to enhance model performance and execution efficiency - Explore new data sources and features that improve predictive power - Contribute to research discussions and clearly communicate findings to the team - Assist in improving research infrastructure, data pipelines, and model robustness Required Qualifications: - Pursuing a degree in Mathematics, Statistics, Financial Engineering, or related field - Strong foundation in probability, statistics, linear algebra, and optimization - Experience with time series analysis, regression, and machine learning techniques - Proficiency in Python (or similar programming language) for data analysis and modeling - Ability to work with large datasets and extract meaningful insights - Interest in equity markets, arbitrage strategies, and systematic investing - Strong problem-solving ability and intellectual curiosity - Excellent communication skills and ability to work in a collaborative environment Required Skills: Probability, Statistics, Linear algebra, Optimization, Time series analysis, Regression, Machine learning, Python, Data analysis, Equity markets, Arbitrage strategies, Systematic investing