Quant jobs / UBS

AI Algo Quant Trader

Research and deploy AI-driven FX-options trading methods at UBS. The role owns models from data research through live pricing, execution and risk monitoring.

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.

Research predictive features in market and trading data.
Backtest ML methods for pricing, quoting and automated hedging.
Deploy validated strategies and monitor drift, costs and risk.
Guide research priorities and mentor quantitative colleagues.

What they ask for

Required

Quantitative degree
Machine learning and time-series methods
Python
Understanding of leakage, overfitting and trading costs
Research-to-production delivery
Technical leadership

Preferred

FX options and electronic market-making
Reinforcement learning or GPU infrastructure

Education: Degree in mathematics, statistics, computing, physics, engineering, quantitative finance or a similar subject; level not specified.
Experience: Proven quantitative or ML production work and research leadership; no minimum years stated.
Languages and tools: Python
NumPy
pandas
scikit-learn
PyTorch
JAX
Markets: fx, options

How to prepare

Backtest an FX-options quoting model with strict chronological splits.
Measure transaction costs, regime sensitivity and out-of-sample decay.
Design monitoring for an automated hedge strategy.

What to study

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

View the posting on UBS’s site ↗

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