Risk Quantitative Models Analyst
4 semanas atrás
About the job RISK Market & Financial Institutions ("MFI") provides the Senior Management of the Group, of the RISK Function and of Corporate & Institutional Banking ("CIB") with full transparency and dynamic analysis and monitoring of market, counterparty, liquidity risks originated and managed by CIB GM and of credit risks on Financial Institutions to assist them in their risk decision making and monitoring.
The RISK MFI Valuation Model Risk Team is the RISK team responsible for the second line of defense on valuation models within Global Markets.
This therefore includes independent review and control of all models used for the generation of official daily P&L and risks.
The team furthermore acts as a center of quantitative expertise within RISK MFI.
Your Main Activities Are Review and approval of Valuation Model, considering suitability, use and set-up, implementation.
Challenging hypotheses, verifying mathematics and reviewing input data and calibration.Comparing model to a challenger model; understanding the associated model risk and potential for model error and its significance; understanding the interaction of the model with the market, the products and the broader portfolio; documenting the review work and communicate it to stakeholders while maintaining a continuous and sound dialogue with them.Regular reassessment and re-review of existing valuation models.Monitor the model performance by developing tools, and implementing performance metrics defined alongside senior analysts.Maintain the mapping between product and models and the associated controls.Ensures model parameters controls in term of levels and the surrounding control framework.Provides quantitative analysis to help in the definition and assessment of the risk management framework for new trades, products and activities that are heavily quantitative or model dependent.Define, maintain and document Valuation adjustments methodologies related to model risk uncertainty and compute their impacts at the appropriate frequency.Propose definition and measurement of model risk at aggregate level of model, portfolio and derivatives product.Collaborate with other teams to achieve the goals of the organization on automation, regulatory topics or risk management.Profile and Skills to Success Bachelor Degree in Engineering / Finance / Mathematics / Sciences / Economics / Econometrics / Computer Science or related.Up to 2 years of experience in Data Analytics or similar.Advanced level of English, both written and oral.Knowledge in Python and MS Office Pack Excel.Attention to detail / rigor.Ability to collaborate / teamwork.Communication skills, both written and oral.Creativity and innovation / problem solving.Client focused.Why joining BNP Paribas? Leading banking institution: BNP Paribas is the European Union's leading bank, and key player in international banking.
It operates in 63 countries and has nearly 183.000 employees, including more than 146.000 in Europe.Our presence in Portugal: In Portugal since 1985, BNP Paribas today has more than 8.700 employees, distributed across the Group's 10 business entities established in the country.
Its presence also extends to 11 excellence centres providing value-added services to various countries where the BNP Paribas Group also operates.International reach: Thanks to its international presence and regular and close collaboration among its different entities, BNP Paribas has the resources to support all clients with financing, investment, savings and protection solutions that help make their projects a success.Diversity and Inclusion commitment: BNP Paribas is an equal opportunity employer and proud to provide equal employment opportunity to all job seekers.Commitment towards work/life balance: At BNP Paribas we care about our employees wellbeing and promote a culture of good integration between work and rest.Remote Working Conditions: At BNP Paribas, we embrace a Smart Working framework based on trust, autonomy and collaboration.Please note that only applications submitted in English will be considered.
In case you are selected for this role, further documentation will be requested to support your hiring process.
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