(Credit Risk) Model Validator - Retail Bank/Mortgages - JN-062022-5634500

Added 02/06/2022

Second person joining the team, informal surrounding
(Credit Risk) Model Validation, IRBA, IFRS9, SAS or Python

About Our Client

My client is a retail bank with offices in Amsterdam and Berlin.

Job Description

Validation of all aspects of Retail Credit Risk models, including new developments, model
changes and periodic validations
Challenging data processing, statistical and business soundness of the model and model
performance
Clear, precise and structured reporting of and defending the validation results
Provide user feedback to improve the model risk framework, including the validation policies and procedures
Presentation of independent model review of Retail Credit Risk Models to Model Governance Committee
Maintain knowledge of model risk and regulatory requirements and standards
Critically assess the operating environment in which models are being developed and deployed
Ensure the effective cooperation of the team across the two locations
Liaison with the UK model validation team Presenting of validation results to the Bank's Model Risk Committee

The Successful Applicant

Qualifications
* Postgraduate qualification in a relevant subject (econometrics, statistics, maths, operational
research), with knowledge of advanced statistical and analytical techniques.

Capabilities
* Proven ability in time management, planning and organizational skills.
* A highly analytical approach to problem solving.
* Ability to assimilate complex information into actionable insights, findings and
recommendations
* Ability to get things done under pressure, hands-on mentality and pro-active.
* Excellent English communication skills both verbal and in writing.

Experience & Knowledge
* Credit risk model validation experience in an ECB or EU regulated institution
* Knowledge and understanding of regulatory modelling requirements for capital and accounting
related credit risk models
* Experienced and competent in the use of SAS, SQL, Python or similar languages/packages.
* Solid knowledge of statistics and econometrics: modelling assumptions, model estimation,
statistical model performance testing