Quant jobs / JPMorgan

Quantitative Trading & Research – Securities Services, Payments and CIB Treasury (Associate/VP)

A data science and ML role in JPMorgan's QTR group supporting securities services, payments and CIB treasury. You use ML and optimisation to improve balance sheet and deposit decisions.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Develop ML-driven analytics and automation with business leads
Build sequential decision tools for net interest income under liquidity and capital limits
Create scalable data architecture for large transaction data
Prototype to production on cloud
Present recommendations to treasury and business stakeholders

What they ask for

Required

PhD or MS in a quantitative field
Machine learning, statistics and maths fundamentals
End-to-end data science in Python
Communication with non-technical audiences

Preferred

Kaggle or GitHub track record
Sequential decision-making experience
LLMs and deep learning
Cloud or HPC

Education: Advanced degree (PhD or MS) in physics, maths, CS, engineering or similar
Experience: Not specified
Languages and tools: Python

How to prepare

Build an end-to-end ML project from data cleaning to a deployed model
Learn reinforcement learning basics and constrained optimisation
Study bank treasury basics: liquidity, funds transfer pricing and net interest income
Practise presenting model results to non-technical audiences

What to study

The Treasury and ALM Quant roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on JPMorgan’s site before applying: requirements, location and pay can change after we check them.

View the posting on JPMorgan’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with JPMorgan and doesn’t handle applications.