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ABOUT THE ROLE Our Model Validation team is responsible for validating Revolut’s risk models and conducting Model Risk oversight. The wide variety of models in Revolut and the responsibilities of the team, make it the unit with the broadest overview of the company-wide analytics and modelling. The activities performed by the team include not only validation of existing models but also building challenger models which test the potential and the efficiency of the existing processes. Key objectives of the function are: (1) assuring that models are reliable, “fit for purpose”, perform adequately and are compliant with internal policies and external regulations, (2) increasing the understanding of a model’s limitations and weaknesses, (3) contributing to ongoing model improvements by e.g. challenging the underlying assumptions. The team publishes detailed validation reports that address these objectives, summarising the model and its limitations, thereby issuing recommendations for model improvement. WHAT YOU'LL BE DOING As a Model Validator you will be performing the following activities:• Perform technical review of risk and business models. Main focus areas are assessing the conceptual soundness, performance and implementation of a model as well as the compliance with regulation and performing quantitative analyses, independent testing and challenging of models.• Writing high quality, detailed validation reports. These include a model risk assessment and recommendations for model improvement. • Interacting with model developers, senior management, internal & external audit, regulators etc, in which your report and recommendations will be discussed and challenged.• Your model scope is broad and includes: regulatory and economic capital, market, credit and operational risk models such as safeguarding reconciliations, VaR, stress tests, IRRBB, EaR, EvE, models used for Risk Appetite Framework, as well as models used for internal business purposes such as predicting client behaviour and supporting management decisions.• Maintaining Model Risk management infrastructure, such as model inventory and validation processes. WHAT SKILLS YOU’LL NEED • University degree in a quantitative discipline, e.g. (financial) mathematics, (theoretical) physics, , economics, statistics/econometrics, machine learning, data science/engineering or similar, at least at Master level. A PhD and/or additional qualification (e.g. second Master degree in one of the disciplines above) is desirable.• At least 2 years of relevant work experience in a quantitative role in the financial industry (e.g. modeller, model validator, quantitative risk manager, quant developer, quantitative consultant) or in tech companies/start-ups as a data scientist/engineer who is eager to gain experience in finance and risk. Core • Knowledge of financial risk measurement and management methodologies• Knowledge of regulatory requirements regarding model risk management and (risk) modelling• Knowledge and experience with mathematical finance and statistics/ econometrics• Knowledge of financial markets & products• Experience with SQL and Python• Good communication and influencing skills to a wide range of stakeholders, full business proficiency in English Desirable - may substitute some of the core skills• Knowledge and experience in data science and implementation of relevant computational algorithms• Knowledge and experience in data/software engineering and of relevant infrastructure.