Quantitative Risk Specialist – Monitoring and Real Estate Valuation
Job Reference #
Do you have experience in credit risk modelling and analytics? Do you enjoy diving into large data sets and using statistical programs to produce valuable insights for quantitative models? Are you an innovative person and a constructive challenger, motivated to contribute to highly specialized solutions?
We’re looking for someone like you to:
•analyse credit data and credit portfolio specifics
•assess and define model specifications
•perform impact and sensitivity analyses
•discuss business requirements, modelling options and impacts with stakeholders
•prepare model documentations and perform model performance and confirmation testing
•support model implementation and changes to productive models
You will be working within Credit Risk Methodology in the Monitoring and Real Estate Valuation team in Kraków. We develop, refine and maintain risk-based monitoring models used to identify credit positions with deteriorating risk profiles in our retail credit books as well as models to estimate the value of real estate securing the mortgage business. We initially develop our models as prototype versions by applying quantitative and statistical approaches, primarily in SAS or R. On project base, we also support the subsequent implementation of the models into the productive IT environment. To effectively design performant solutions we have to develop a deep understanding of the portfolio specifics, products and respective markets and actively collaborate with different areas in the bank including departments in Risk Control, Front Office and IT.
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.
•Master's degree or equivalent education in a quantitative field (e.g. data science, statistics or other discipline with quantitative background) as well as relevant work experience
•strong analytical and conceptual skills combined with good statistical understanding
•experience in programming and the use of statistical software (e.g. Python, R, SAS)
•practical application of statistical procedures, in particular machine learning, is a plus
•having worked with large data sets and relational databases using SQL querying is a plus
•understanding of financial markets and products, know-how of real estate markets and valuation methods is a plus
•good communication skills and the ability to translate complex and technical problems into a clear and intuitive language
•open, collaborative and pro-active personality who is able to work and plan independently
•able to deliver high quality results against tight deadlines in a fast paced and interdisciplinary environment
•fluent in English, German is a plus
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?
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.