Quantitative Risk Specialist, Risk Methodology

Recruiter
UBS
Location
London, United Kingdom
Salary
Competitive
Posted
04 Oct 2022
Closes
08 Oct 2022
Ref
17160899
Job Function
Risk Management
Industry Sector
Finance - General
Employment Type
Full Time
Education
Bachelors
Your role
Does quantitative modelling excite you? Are you an innovative thinker and interested in risk topics? Do you know how to work well within a team to develop and deliver high quality solutions?

We are looking for a Quantitative Risk Specialist (Risk Methodology) like you to:

• develop and maintain CCAR / CECL methodologies for our Securities Backed Lending (SBL) portfolio in the US
• bring innovation to Risk Methodology Group in the development, refinement and implementation of risk models
• collaborate with risk officers, business managers, Risk IT, Change Operations and other stakeholders supporting the proper implementation and execution of risk models and support regulatory exercises
• interact with our independent validation team and address their queries Your team
You'll be working in our Securities Backed Lending (SBL) team within Credit Risk Methodology in London, Your main responsibilities will be to maintain and refine CCAR / CECL models covering our SBL business. The framework captures all SBL businesses world-wide ranging from retail clients to complex structured lending solutions for UHNW clients with derivative exposures.

You will be working with key stakeholders within our Global Wealth Management business on both the risk and business side to deliver state-of-the-art methodologies and support new business initiatives, as well as work with models implemented on the Cloud.

Diversity helps us grow, together. That's why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.

Your expertise
• a Master's or PhD degree in an applied quantitative discipline (e.g. Econometrics, Statistics, Financial Engineering, Economics, Finance)
• ideally 5+ years' of experience in credit risk modelling or other areas of risk methodology and/or model development
• sound knowledge of statistical and econometric methods and their application
• previous experience with SBL models is a plus
• previous experience and ability to implement models in a programming language (e.g., R, Python) is essential
• experience with handling large datasets and working with the Cloud is a plus
• strong analytical, conceptual and organizational skills with the ability to work under tight deadlines
• interest in placing model development activities within the bigger picture of the organization
• ability to influence and convince key stakeholders within the model development process

*LI-GB

*EFC-UBS

About us
UBS is the world's largest and 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.

With more than 70,000 employees, we have a presence in all major financial centers in more than 50 countries. Do you want to be one of us?

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.
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