Quantitative Risk Analyst/Econometrician
Job Reference #
Are you adept at risk matters? Are you interested in working in a team of quants and econometricians? Do you know how to work well within a team to develop and deliver solutions? Then we are looking for you to:
• create, develop and maintain methodologies for internal and regulatory stress scenario expansion for UBS
• use techniques from quantitative risk management, statistics, financial econometrics and macroeconometrics to develop, assess, and change models
• implement models in R/Python and produce clear and detailed documentation for regulators across the globe
• bring new quantitative modelling ideas to our team to push ahead key projects within the bank
You’ll be working in Scenario Models team within Forecasting and Scenario Methodology in Krakow with members in the US, UK, Switzerland, Poland, and India. Our role is to develop and maintain financial and macroeconometric forecast models that are used in stress scenarios, to assess the impact of macro-economic and market scenarios on the firm’s profitability and capital adequacy. Our deliveries are key to regulators across the globe, used for accounting standards, and internal capital assessments and business planning. The framework captures all risk types across all businesses world-wide.
• a Master's or PhD degree in applied quantitative discipline (e.g. Quantitative Economics, Econometrics, Statistics, Financial Engineering, Computational Science, Quantitative Finance)
• experience in building models from scratch (e.g., time series analysis, linear/non-linear models, Gaussian/non-Gaussian models, parametric/non-parametric models)
• sound knowledge of statistical and econometric methods and their application
• proficient in programming with statistical software. Python & R is strongly preferred
• strong analytical, conceptual and organizational skills with the ability to work to tight deadlines
• general understanding and interest in (macro-) economic mechanisms and their influence on financial markets
• a clear understanding of the following terms: MonteCarlo, bootstrap, stationarity, co-integration, regression, goodness of fit, out-of-sample, null hypothesis, p-value, risk-neutral, autoregressive, quantiles, density function
• great in communicating (and you know how to handle challenging situations)
• a team-player, but able to complete tasks autonomously
• fluent in English, additional languages are welcome
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
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.