Quantitative Analyst / Data Scientist Principal Manager

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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 121,000 professionals working in multidisciplinary teams with profiles as diverse as financiers, legal experts, data scientists, developers, engineers and designers.

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The Global Markets Risk Unit (GMRU) Center of Excellence (COE) plays a crucial role in enhancing risk management within BBVA’s trading activities. It consists of a hybrid team of data scientists and quantitative analysts, leveraging machine learning and data technologies to improve risk assessment and mitigation strategies. The unit is responsible for developing mathematical models and tools for market risk evaluation, counterparty credit risk (XVA), stress testing, and automated model calibration. It also ensures risk-sensitive limit frameworks and assesses front-office models for accuracy. Beyond technical responsibilities, the team collaborates closely with risk managers, quantitative teams, and data specialists to ensure methodologies align with regulatory standards, improve valuation models, and automate processes to reduce operational risk. Additionally, the COE promotes quantitative knowledge sharing across the organization to drive innovation in financial risk management​.

About the job:

This role will be responsible for the continuous improvement of market risk and counterparty risk measurement and management processes. Additionally, the role will centralize and strengthen the presence of the Center of Excellence (COE) in strategic risk projects, ensuring alignment with best practices and regulatory frameworks. The ideal candidate will bring deep quantitative expertise, hands-on experience in risk modeling, and strong programming skills to enhance risk analytics and automation.

Qualifications

• 10+ years of experience in a quantitative role within a financial institution, preferably in risk management, quantitative analytics, or trading.

• Expert knowledge of derivatives pricing, market risk, and counterparty credit risk in global financial markets.

• Strong programming skills in C++, C#, and Python, with hands-on experience in implementing quantitative models.

• Understanding of machine learning techniques and their applications in risk management and financial modeling.

• Familiarity with risk regulations (e.g., Basel III, FRTB, SA-CCR, ISDA SIMM) and risk capital frameworks.

• Excellent problem-solving skills with the ability to interpret complex data, perform quantitative analysis, and communicate insights to stakeholders.

• Master’s or PhD in Quantitative Finance, Financial Engineering, Mathematics, Statistics, or a related field is preferred.

Skills:

Customer Targeting, Empathy, Ethics, Innovation, Proactive Thinking