Quant jobs / JPMorgan

Quantitative Trading & Research – Securities Services (Analyst/Associate)

A data science and ML role in JPMorgan's QTR group serving the securities services business. You build ML and optimisation tools for deposit and net interest income decisions rather than trade markets.

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 to optimise net interest income under balance sheet constraints
Design scalable data architecture for transaction data
Prototype and take projects through to production
Present findings with data visualisation

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; early-career
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 optimisation under constraints
Study how banks manage deposits, liquidity and net interest income
Practise presenting model results to non-technical audiences

What to study

The NLP and ML Quant Researcher 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.