Quantitative Trading & Research (QTR) is an expert group in J.P.Morgan specializing in statistical modelling, data analytics, balance sheet optimization and other quantitative methods to support the Commercial and Investment Bank (CIB). The QTR Securities Services team applies cutting-edge AI/ML techniques to fundamentally transform the way we do business by enabling business revenue growth and efficiency within the CIB organization.
Job Summary
As an Analyst / Associate in the QTR Securities Services team, you will support the 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
Build up a scalable data architecture to handle the large volume of transaction dataAutomate existing manual processes and build tools to enable the business to optimize their decision making and deposit management
Build sequential decision making tools to optimize the net interest income of the business under various liquidity, capital and balance sheet constraints
Drive projects end-to-end, from brainstorming, prototyping, data processing, data analysis to model development
Make real-world, commercial recommendations through effective presentations to various stakeholders
Leverage data visualization to communicate quantitative insights to help business decision-making
Work closely with colleagues in Quantitative Research, Technology and the Chief Data and Analytics Office (CDAO) to drive the CIB 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
Participation in KDD/Kaggle competition, Hackathons or contribution to GitHub
You demonstrate hands-on experience in solving sequential decision making problems
Experience in applying LLMs and/or deep learning methods to solve business problems
Experience in working with Cloud and/or HPC environments
