Disclaimer: Hunt UK Visa Sponsors aggregates job listings from publicly available sources, such as search engines, to assist with your job hunting. We do not claim affiliation with UBS. For the most up-to-date job details, please visit the official website by clicking "Apply Now."
Job Reference #
309441BR
Job Type
Full Time
Your role
Are you an experienced quantitative analyst with experience in derivatives pricing, risk and data science?
Are you in innovative thinking, have analytical mindset, enjoy creating analytics and building analytical tools?
We are looking for someone who can work closely with trader and sales, blending top analytical methods and cutting edge technologies to automate the desk by providing fast time-to-market desk solutions.
- You will be participating in the design and development of advanced analytics and full stack solutions used by Front Office to enhance desk automation levels and revenue generating capabilities, this includes:
- Working as part of the team to create the next generation automated hedging solution for the QIS desk
- Working as part of the team to redesign and automate QIS strategies
- Working as part of the team developing the next generation Trading and structuring pricing capabilities.
- You will be expected to closely liaise with trading, sales, structuring and the technology groups in the Equity Derivatives and QIS business.
- You will be able to rapidly learn in-depth knowledge and gain experience of Equity Derivatives and QIS trading / risk management by creating new tools and solutions with the business.
Your team
You’ll be working within the ACQA Quant Platform team working with the wider QIS platform and algo quant teams, Quant Core platforms & Valuation model quant teams globally. In addition, you will be working closely with global business stakeholders to elicit and review requirements
Your expertise
- This position is open to professionals with at least 4 years of experience. Exceptional candidates with less experience can be considered.
- Minimum Bachelor/Masters degree from a recognized University. Computer Science / Mathematics / Physics / Engineering majors preferred.
- Strong problem solving and analytical skills with prior experience in applying machine learning and statistical techniques to solve business problems.
- Strong technical skills in at least one scripting language (Python preferred) and one core language (C++ preferred)
- An excellent team player with a good balance of strategic view & rapid solution development.
- Solid background in data structure and algorithms.
- Knowledge of QIS or Equity Derivatives business will be a plus.
- Knowledge of KDB, Kafka, Kubernetes, Docker will be a plus.
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 embrace flexible ways of working when the role permits. We offer different working arrangements like part-time, job-sharing and hybrid (office and home) working. Our purpose-led culture and global infrastructure help us connect, collaborate, and work together in agile ways to meet all our business needs.
From gaining new experiences in different roles to acquiring fresh knowledge and skills, we know that great work is never done alone. We know that it's our people, with their unique backgrounds, skills, experience levels and interests, who drive our ongoing success. Together we’re more than ourselves. Ready to be part of #teamUBS and make an impact?
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.
Your Career Comeback
We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.
