Quantitative Trading & Research – Securities Services and Payments – Associate or Vice President

JPMorgan Chase & Co.; Greater London; On-site; GBP 120,000 - 170,000; Full time

Job summary

JPMorgan Chase & Co. in London seeks an Associate or VP in the Quantitative Trading & Research group to tackle technically complex problems, from AI/ML applications for pricing to large data processing using cloud capabilities.

You will partner with business leads, build scalable data architectures, automate processes, and drive end-to-end projects, delivering data-driven insights to optimize revenue and manage risk.

Qualifications

• Advanced degree in a quantitative field (PhD or MS).
• Strong foundations in ML, statistics and mathematics.
• End-to-end data science experience using Python.
• Excellent communication and ability to present to non-technical audiences.
• Passion for learning, knowledge sharing and collaboration.

Responsibilities

• Develop AI/ML analytics and automation to support business goals.
• Build scalable data architectures for large transaction datasets.
• Automate manual processes and create decision-support tools.
• Develop sequential decision making for net interest income optimization.
• Drive projects end-to-end from ideation to production.
• Present commercial recommendations to stakeholders.
• Visualize data to communicate quantitative insights for decisions.
• Collaborate with Quantitative Research, CIB Treasury, CIO, and CDAO to advance data strategy.

Skills

Quant field MS/PhD

ML & Stats

Python

Communication

Collaboration

Education

MS/PhD in quantitative field

Job description

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 and Payments 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 Associate or a Vice President in the Quantitative Trading & Research (QTR) Securities Services and Payments, you will support the business in tackling their most technically complex business problems to optimize revenue and manage risks. This could range from developing AI/ML applications that make business-critical predictions such as client pricing, to handling vast data sets using the J.P.Morgan's Cloud capabilities or optimal hedging policies for interest rate risk management. 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 data.
• Automate 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, CIB Treasury, Chief Investment Office, 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.