KDB+/Q Quantitative Developer

UBS; London; On-site; GBP 60,000 - 90,000; Full time

Job summary

UBS is seeking a professional for their Global Markets Quantitative Analytics team in London. The role involves algorithmic trading analytics, requiring expertise in kdb+/q, Python, and data science. The ideal candidate will work on global projects to enhance analytics and analyze performance for clients. This position offers a collaborative and inclusive work environment with opportunities for career growth.

Qualifications

• Experience in designing and building algorithmic trading analytics.
• Well-versed in modern software development practices.
• Proficient in at least one programming language (Python, MATLAB, R).

Responsibilities

• Work closely with Global Markets and Technology teams.
• Analyze algo performance for clients and deliver reports.
• Translate business requirements into designs for global solutions.

Skills

Algorithmic Trading

Data Science

Communication Skills

Education

Degree in Computer Science

Degree in Engineering

Degree in Physics

Degree in Mathematics

Tools

kdb+/q

Python

MATLAB

R

Job description

Job Reference #

318539BR

City

London

Job Type

Full Time

Your role

Are you interested in algorithmic trading? Are you an innovative thinker who enjoys building tools?

• Work closely with products across Global Markets including Equities, Futures, and FX, and Technology to deliver regional and global projects
• Help design and enhance analytics for the Equities
• Analyze algo performance for clients, including highly bespoke, in-depth reports
• Translate business requirements into designs for global solutions

Your Career Comeback

We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.

Your team

You will be working in the Global Markets Quantitative Analytics and Development team. Our role is to provide tools, analytics, and execution consultancy for Execution Services and Electronic Trading for Equities, Futures, and FX products globally. Our team is responsible for building top-grade, high-performance client analytics and data.

Your expertise

• At least one degree in computer science, engineering, physics, or mathematics
• Experience in kdb+/q
• Well-versed in Computer Science fundamentals, modern software development practices, Unix utilities
• Proficient in at least one of Python, MATLAB, or R
• Experience in designing and building algorithmic trading analytics, market data, and modeling market microstructure
• Good understanding of data science, market dynamics, and ability to explain, visualize, and work with data
• Experience in global Equities, Futures, Options, and/or FX products and data is a plus
• Strong communication skills

*LI-GB

About us

UBS is the world’s largest and the only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management, and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.

We have a presence in all major financial centers in more than 50 countries.

Join us

At UBS, we know that it's our people, with their diverse skills, experiences, and backgrounds, who drive our ongoing success. We’re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow, and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. We also recognize that great work is never done alone. That’s why collaboration is at the heart of everything we do. Because together, we’re more than ourselves.

We’re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.

Disclaimer / Policy statements

UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills, and experiences within our workforce.