Quant jobs / MUFG

Associate, Systematic Credit Research Quant

A research quant role building models and relative value strategies for credit products and working with the trading desk to run them systematically. It is research-heavy and deadline-driven.

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 credit risk models and systematic trading algorithms
Research relative value signals across CDS, bonds and structured products
Build scalable frameworks for real-time credit risk assessment
Work with the desk to put strategies into live use
Deliver research against market-driven deadlines

What they ask for

Required

PhD in maths, physics, computer science or financial engineering
Statistical inference and machine learning
Advanced Python
Stochastic calculus
Time series analysis
Optimisation methods

Preferred

CDS, bonds and structured products familiarity
Numerical methods

Education: PhD in maths, physics, computer science, financial engineering or a related field.
Experience: Not stated beyond PhD-level research ability
Languages and tools: Python
Markets: credit, fixed-income

How to prepare

Study how CDS and bond spreads are modelled and compared
Backtest a simple credit relative-value signal in Python
Revise stochastic calculus and time-series methods used in credit
Practise writing short research notes on a trade idea

What to study

The Quantitative 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 MUFG’s site before applying: requirements, location and pay can change after we check them.

View the posting on MUFG’s site ↗

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