Global Market Risk Unit Quantitative Manager Cib

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BBVA is a global company with more than 160 years of history that operates in more than 25 countries where we serve more than 80 million customers. We are more than 121000 professionals working in multidisciplinary teams with profiles as diverse as financiers legal experts data scientists developers engineers and designers.

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TheGlobal Markets Risk Unit (GMRU)area is responsible for the measurement control and management of market and counterparty credit risks valuation adjustments (XVA) calculation of economic capital across BBVAs global market positions as well as fair value valuation independent price verification and quality assessment of Front Office quantitative models. All these activities are performed in accordance with applicable international regulatory frameworks and sound risk management practices.

In close coordination with quantitative analytics teams located in Front Office and other risk departments theGMRU Advanced Analytics Teamdevelops the quantitative methodologies and tools required to execute GMRU core processes and leads key projects related to regulatory change. The team brings together quantitative analysts and data scientists to drive innovation in risk modeling.

About the job:

About you

You hold a strong quantitative and analytical background with a keen interest in mathematical modeling within practical financial environments. You are passionate about applying data science quantitative finance and machine learning to financial risk management. You enjoy programming building scalable risk software and working in cross-functional environments. You possess excellent communication skills to interact effectively with diverse technical and executive stakeholders and you excel as a collaborative team player.

As aData Scientist Manager your primary responsibilities will include:

• Model Development & Methodology:Design develop and implement advanced mathematical models data-driven methodologies and quantitative tools for measuring and managing market and counterparty credit risks associated with Global Markets products.

• Risk Scope & Metrics:Drive quantitative initiatives covering market risk metrics (VaR Stressed VaR FRTB framework) counterparty credit risk measurement (IMM PFE) valuation adjustments (XVA) and economic and regulatory capital calculations.

• Stakeholder Collaboration:Partner closely with Risk Managers within the Global Risk Management Unit to ensure alignment with regulatory frameworks (ECB EBA EBA/FRTB) and sound risk practices. Collaborate with Front Office quantitative teams to validate and align valuation models.

• Software Architecture & Testing:Enforce code development policies software architecture standards and rigorous testing frameworks (CI/CD unit testing) to ensure robust maintainable and reusable codebase across teams.

• Leadership & Project Management:Lead technical workstreams within regulatory transformation projects mentoring junior quantitative analysts and data scientists.

Qualifications & Requirements

Education:

• Required:University Degree (Bachelors or Masters) in Mathematics Physics Quantitative Engineering Actuarial Sciences Quantitative Economics or a related STEM field.

• Highly Valued:Masters degree or Ph.D. in Quantitative Finance Financial Engineering Artificial Intelligence Big Data or Applied Mathematics.

Professional Experience:

• Minimum 6 years of professional experiencein quantitative risk analysis financial engineering or data science applied to banking investment banking or capital markets.

• Proven track record in market risk modeling counterparty credit risk XVA or pricing derivatives within investment banking / corporate banking units.

Key Skills:

• Financial & Risk Expertise:Solid understanding of financial markets derivative pricing (fixed income credit inflation) risk management concepts (market and counterparty credit risk related) and regulatory risk frameworks (FRTB IMM).

• Programming & Tech Stack:Advanced proficiency in at least one object-oriented or data programming language:Python(NumPy SciPy Pandas PyTorch/TensorFlow)C orC#.

• Data Science & ML:Practical experience with machine learning techniques applied to quantitative finance (e.g. anomaly detection calibration optimization).

• Software Engineering:Familiarity with Git version control continuous integration/continuous delivery (CI/CD) pipelines and containerization (Docker).

Languages:

• English:B2 (Advanced/Fluent)or higher (written and spoken) as this position operates in a global environment with international stakeholders.

Skills: