Euronext Clearing

15 ott - Italia
Cassa di Compensazione e Garanzia

Join us as a Model Risk – Specialist Are you ready to shape the future of capital markets? We are looking for a Model Risk – Specialist to join the Model Risk LOD2 Team in Rome. This is a position offering an exciting opportunity to contribute to our mission. Ccnl credito Ral starting from 50.000€
Key accountabilities
- Independently validate the risk models designed by LoD1 used to measure market, credit risk and liquidity risk
- Develop and maintain independent Python replications of margin and stress testing models, used to benchmark results and to run challenger analyses
- Timely analyse significant changes to a model through a standardized approach and issue recommendations/suggest alternatives
- Design and perform sensitivity analyses, backtesting, anti-procyclicality and stress testing analyses
- Input data validation, implement process improvements to streamline data analysis and reporting
- Liaise with Regulators for MV topics
- Interact effectively with model designers and model developers, as well as with external consultants supporting validation activities




- Present findings and recommendations to management and stakeholders, and draft independent validation reports to internal and supervisory standards

Knowledge, Skills and Experience
- Master's Degree in Quantitative Finance, Engineering, Mathematics, Statistics, Physics or equivalent
- Strong knowledge of financial markets and instruments, pricing, risk indicators
- 5-7 years of work experience in the banking or financial services industry, including regulators or consultancy firms; experience with Clearing Houses is a plus
- Solid grounding in market risk quantitative techniques (VaR and Expected Shortfall estimation and related backtesting tests)
- Familiarity with the EMIR regulatory framework and ESMA technical standards is a plus
- Proficiency in Microsoft Office package
- Strong knowledge of programming languages (e.g. Python, SQL, Julia…), with the ability to build and document quantitative m

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