EMEA Quant Trader: Data-Driven, Automated Markets

UBS; Greater London; On-site; GBP 120,000 - 190,000; Full time

Job summary

UBS in London seeks a quant trader for the CRB desk to drive data-driven, systematic trading across equities and ETFs. You will design, back-test and implement strategies, while supporting pricing and risk models in a fast-paced, collaborative environment.

The role requires 5+ years of relevant experience, strong Python skills, and the ability to work independently within UBS's global markets team.

Qualifications

• You’re curious to explore how AI can improve how we build, deliver, and optimize workflows.
• Great problem-solving and analytical ability.
• 5+ years of relevant experience.
• A self-starter who can work independently.
• Excellent communication skills including the ability to quickly and easily understand and explain business, software, and modelling issues.
• Excellent interpersonal skills.
• A high degree of integrity, comfortable to challenge and who collaborates naturally.
• Ideally, experience in the quant trading space especially in equities and/or ETFs.
• Excellence in statistical modelling and data science.
• Experience in python essential. KDB/Java/C++ would be beneficial
• Experience with Unix systems and familiarity with DevOps practices considered a plus

Responsibilities

• Manage the team book and automated processes.
• Apply a data-driven and systematic approach to trading.
• Employ statistical analysis to optimize quoting, trading, and risk management strategies.
• Involve in designing, back testing, and implementing trading strategies as well as tracking their performance.
• Contribute to pricing and risk models and oversee their operation.

Skills

5+ years experience

Python

KDB/Java/C++

Unix

DevOps

Communication skills

Problem solving

Data science

Statistical modelling

Equities/ETFs experience

Job description

UBS in London seeks a quant trader for the CRB desk to drive data-driven, systematic trading across equities and ETFs. You will design, back-test and implement strategies, while supporting pricing and risk models in a fast-paced, collaborative environment.

The role requires 5+ years of relevant experience, strong Python skills, and the ability to work independently within UBS's global markets team.