Quantitative Risk Specialist

Germany
- Risk
- Group Functions

**Job Reference #**
- 257918BR

**City**
- Frankfurt am Main

**Job Type**
- Full Time, Part Time

**Your role**
- Are you experienced in data analysis and/or risk models, in particular in the area of Credit Risk or you have relevant academic background in this area? Are you an innovative thinker that likes challenge and is able to deliver against tight timelines? Do you enjoy working with data and develop your own codes?
- We're looking for someone like you to:
- Drive the European Bank Association Stress Testing exercise on the topic of Expected Credit Loss, covering the fields along data sourcing, analytics and governance
- Provide end-to-end analytics on top-contributors and summary statistics to investigate potential data anomalies or wrong data entries and mitigate with responsible stakeholders
- Assume responsibilities in the Model Data Control Standards (MDCS) program for building an overarching control framework covering all relevant credit risk models, ensuring implementation and monitoring of model specific controls.
- Take responsibilities for the analysis and oversight of the IFRS9 Expected Credit Loss across all divisions
- Support our team in fulfilling the mandate to act as a central instance between quantitative modelers, Risk Control, IT departments, and Finance

**Your team**
- You’ll be working within the Credit Risk Methodology teams in Frankfurt, which are part of group-wide UBS Risk Methodology. Our role is to develop and maintain all firm-wide credit risk models.
- 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 university degree (such as Mathematics, Statistics, Econometrics or Computer Science) and a minimum of 5 years of prior work experience in a credit risk environment with experience in regulatory practice
- Prior experience from European Bank Association Stress Testing with an understanding of the underlying portfolios and key drivers of the ECL
- Knowledge of high-level programming languages, and experience with statistical modelling software (e.g., SAS, R, Python)
- Ability to work with large data sets and experience with relational databases (very good command of SQL)
- Prior experience with monitoring data flows and calculation processes would be beneficial, ideally in an environment with sophisticated system interactions
- Proven experience communicating with non-technical stakeholders and translating technical concepts into business terms
- Pro-active in taking new initiatives and carrying them through completion
- Fluent in English, both in oral and written form

**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.