Senior Quantitative Credit Risk Modeler 100% (f/m/d)

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.
You will be a member of the Credit Models team within the Financial Portfolio Risk Management & Control unit of CRO and you will be responsible for development, maintenance and enhancement of credit risk models, i.e. internal credit risk rating approaches (PD, LGD), IFRS 9 Expected Credit Loss (ECL) models and credit loss stress testing models, covering the end-to-end credit models lifecycle.
YOUR CHALLENGE
Develop state-of-the-art credit risk models, i.e. internal credit risk rating approaches (PD, LGD), IFRS 9 Expected Credit Loss (ECL) models and credit loss stress testing models across all relevant portfolios using statistical methods
Interact regularly with subject matter experts from Credit Risk Management and other functions to ensure that model user requirements are properly reflected and translated into high-quality models
Provide model prototypes applying standard coding language for impact analysis and model implementation testing
Prepare high-quality model documentations and materials in line with the Group’s model risk governance framework
Collaborate closely with the Model Validation team during the independent model review and remediate potential validation findings
Execute the regular model performance monitoring, backtesting and benchmarking
Drive innovation through the adoption of advanced quantitative techniques – including interpretable machine learning applications – while maintaining transparency, auditability and regulatory acceptance
Support the implementation of new models and model changes into the Group’s IT infrastructure
Act as subject matter expert for all credit model related questions from users across Credit Risk Management and Front Office
YOUR PROFILE
Master’s degree in a quantitative area, such as Mathematics, Statistics, Econometrics, Quantitative Finance
Professional qualifications such as FRM or CFA are considered an advantage
Minimum of 5 years of relevant experience in credit risk modelling within a financial institution, ideally with wealth management credit products knowledge
Proven hands-on experience in developing and maintaining credit risk models as well as demonstrated expertise in statistical and econometric methods
Expertise in large data querying and analysis
Strong proficiency in programming, e.g. in Python or R
Results-oriented mindset with excellent analytical and problem-solving skills
A collaborative, customer-focused attitude with experience in cross-functional teamwork
Outstanding interpersonal and communication skills, with fluency in English (written and spoken)
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Skills
Python, Machine Learning, Risk Management, Wealth Management