Model Validator Quantitative Analyst
Poland
Risk
Group Functions
Job Reference #
258565BR
City
Kraków
Job Type
Full Time
Your role
Are you an expert in analytics? Are you an innovative thinker who likes to challenge the status quo? Do you know how to work well within a team and deliver effective solutions? We're looking for someone like that to carry out independent validation of models used in UBS’ PPNR area, by
• assessing the model's conceptual soundness and methodology
• checking appropriateness of input data, model assumptions and parameters, calibration accuracy as well as of qualitative or expert adjustments, etc.
• reviewing outcome, impact, performing benchmark and robustness analyses
• identifying model limitations and evaluating overall model risk
• documenting the assessment to required standards
• interacting and collaborating with stakeholders such as model developers, users, model governance representatives in order to safeguard the quality of our model risk management framework
Your team
You’ll be working in the Model Risk Management & Control US team responsible for the independent validation of the CCAR PPNR models used in UBS used in the US entity. The models are used for stress testing. Our role is to understand and assess the risks associated with the use of models throughout our firm. We are responsible for identifying corrective actions that promote model risk management process improvements and ensuring the timely remediation of identified issues. Our team interface with key stakeholders, US regulators and internal auditors to discuss justification and reasoning behind validation and review findings.
Your expertise
• MSc degree in quantitative Finance, Mathematics, Physics, Statistics, or quantitative Economics; PhD is a plus
• 1~2 year’s working experiences in model validation or model development, in a bank or a consulting firm, e.g. “Big 4” or analytics / model risk consultancies)
• knowledge of financial markets and products, strong interest in the financial services industry, preferably in risk management. Prior experience with PPNR models is a plus
• knowledge of investment banking, wealth management is a plus
• knowledge and experiences in statistical and economic modeling techniques, ie. regression, logistic regression, time series, error correction model etc.
• strong coding skills in excel, SAS, R, Python, MATLAB or similar
• excellent analytical skills
• curiosity and a thirst for innovation
• fluent in English, oral and written
• a team player with strong interpersonal skills
• motivated, well organized and able to complete tasks independently to high quality standards
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?
How we hire
This role requires an assessment on application. Learn more about how we hire: www.ubs.com/global/en/careers/experienced-professionals.html
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.