Posting description

Quantitative Research (QR) is an expert group in J.P.Morgan specializing in statistical modelling, data analytics, and other quantitative methods. In Securities Services, QR applies cutting-edge AI/ML techniques to fundamentally transform the way we do business.

As an Associate in the QR Securities Services team, you will support the Custody and Fund Services business in tackling their most technically complex business problems. This could range from leveraging LLMs to deliver capabilities at scales never before possible, to developing ML applications that make business-critical predictions, to handling vast data sets using the J.P.Morgan's Cloud capabilities. You will be in tight partnership with the business in identifying their most pressing pain points and iterating towards a solution that really works for them. If you are passionate about solving real-world problems using your quantitative background and experience, this may be just the team for you.

Job responsibilities

Work with business leads to develop AI/ML-driven analytics and automation that support their business goals Perform large-scale analysis on our proprietary dataset to solve problems never tackled before Test ideas, figure out what works, and write production code to make that idea work for the business Make real-world, commercial recommendations through effective presentations to various stakeholders Work closely with colleagues in Quantitative Research, Technology and the Chief Data and Analytics Office (CDAO) to drive the Securities Services data strategy forward

Required qualifications, capabilities, and skills

Advanced degree (PhD or MS) or equivalent in a quantitative field: Physics, Mathematics, Computer Science, Engineering, etc. Robust understanding of Machine Learning, Statistics, and Mathematics, both in fundamentals as well as in application. Experience in tackling real world data science problems, end-to-end from prototype to production, using Python. Excellent communication skills (both verbal and written) and the ability to present findings to a non-technical audience. Passion for learning, sharing knowledge, building collaborations, and getting things done.

Preferred qualifications, capabilities, and skills

Experience in applying LLMs and/or deep learning methods to solve business problems. Experience in working with Cloud and/or HPC environments.