Quantitative Research

Role Overview: You have the exciting opportunity to join a dynamic and growing team in a fast-paced and challenging area as a Quantitative Research Associate/Vice President within the Quantitative Research Group at a leading financial firm in Mumbai. In this role, you will partner with the Business to provide a comprehensive view and support the activities of the Quantitative Research Group across asset classes globally. Your work will play a critical role in providing effective, timely, and independent assessments of the Firm's booking models of exotic structures and help develop new models as necessary. You will be part of a team that transforms business practices through data science and other quantitative methods, contributing to JP Morgan's position as a dominant player in handling trillions of dollars of client assets. Key Responsibilities: - Perform large-scale analysis on the proprietary dataset to solve previously unaddressed problems. - Identify new insights to drive feature modeling for nuanced insights generation. - Develop models end-to-end, from prototype to full-scale production. - Provide real-world, commercial recommendations through effective presentations to various stakeholders. - Utilize data visualization to communicate data insights and results effectively. - Document and test new/existing models in collaboration with control groups. - Implement models in Python-based proprietary libraries. - Provide ongoing desk support. Qualifications Required: - Master's or Ph.D. degree program in computer science, statistics, operations research, or other quantitative fields. - Strong technical skills in data manipulation, extraction, and analysis. - Fundamental understanding of statistics, optimization, and machine learning methodologies. - Ability to build models end-to-end, from prototype to full-scale production, utilizing ML/big data modeling techniques. - Knowledge in developing models on cloud infrastructure. - Integration and utilization of LLM models for advanced model development and enhancement. - Basic knowledge of financial instruments and their pricing. - Mastery of software design principles and development skills using one of C++, Python, R, Java, Scala. - Previous practical experience in solving machine learning problems using open-source packages. - Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience.,