Wholesale Credit Risk Models Specialist

We are looking for two quantitative professionals who combine technical depth with the ability to lead complex initiatives and generate impact across different areas and geographies.

• Great analytical and problem-solving capacity, with the judgment to question methodologies and transform complex problems into robust quantitative solutions.
• A level of autonomy and responsibility, with the ability to take ownership of several complex workstreams simultaneously.
• Solid organization and project management skills, prioritizing effectively in demanding and changing environments.
• Ability to influence and collaborate with stakeholders from different functions, levels of responsibility, and geographies.
• A collaborative leadership style, with a willingness to develop other professionals, share knowledge, and contribute to building a high-performance team.
• Intellectual curiosity and an orientation toward continuous improvement, with an interest in new analytical methodologies, technologies, regulatory developments, and industry best practices.
• Excellent communication skills and the ability to explain sophisticated quantitative concepts in a clear and pragmatic manner.
• A proactive attitude and the ability to identify risks, opportunities, and areas for improvement beyond the immediate scope of assigned projects.
• University degree in Mathematics, Statistics, Physics, Engineering, Computer Science, Data Science, Actuarial Science, Economics, or another relevant quantitative discipline. A Master's or PhD will be particularly valued.
• 3 to 8 years of relevant professional experience in credit risk modeling, model validation, quantitative risk management, or related fields, with significant experience in wholesale credit risk.
• Solid and practical experience in the development, validation, monitoring, and/or implementation of wholesale credit risk models, including ranking models and/or PD, LGD, and EAD parameter models.
• Solid knowledge of IRB and IFRS9 frameworks, including development requirements, performance evaluation, calibration, documentation, governance, and regulatory expectations.
• Demonstrable experience in regulatory or model remediation initiatives of high complexity, such as IRB model modifications, EBA-related programs, Return to Compliance, supervisory findings, or IFRS9 model development and validation programs.
• Advanced knowledge of statistical modeling and Machine Learning techniques, especially applied to credit risk classification and ranking, parameter estimation, forecasting, and model performance evaluation.
• Solid knowledge of programming and data analysis, especially in Python, SQL, R, and/or equivalent analytical environments.
• Experience working with large and complex datasets and good knowledge of aspects related to data quality, traceability, and information requirements for modeling. Demonstrated ability to lead complex projects and coordinate multiple stakeholders, managing priorities, dependencies, deadlines, and deliverables in an international environment.
• Experience reviewing or guiding the work of other quantitative professionals and providing technical mentoring and methodological challenge.
• Excellent oral and written communication skills, with the ability to explain complex technical and regulatory issues to both specialized and non-specialized audiences.
• Fluent English level, oral and written.

• Experience in interacting with supervisors, regulators, Internal Validation, Model Risk Management, or Audit on model-related matters.
• Experience in IRB Roll-out, Return to Compliance, EBA Repair Programs, model reviews by the ECB, or other similar regulatory initiatives.
• Deep knowledge of wholesale credit products and portfolios and their main risk drivers, including Large Corporates, Financial Institutions, Sovereigns, and other specialized portfolios.
• Experience with Artificial Intelligence and advanced Machine Learning techniques, especially in their application within regulated risk modeling environments.
• Experience with cloud analytical platforms, especially AWS, as well as with the industrialization or automation of model development and monitoring processes.
• Familiarity with alternative and non-traditional data sources, including external credit information, transactional information, client networks, and unstructured data.
• Experience working in international and multicultural environments, coordinating teams from different countries or business units.

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Within GRM Data & Analytics, the Wholesale Credit Risk Models & Parameters team is responsible for the development, maintenance, monitoring, and continuous improvement of risk ranking models and credit risk parameters for wholesale portfolios, ensuring robust methodologies, adequate risk differentiation, regulatory compliance, and their correct integration into BBVA's risk management processes.

As a member of the GRM Data & Analytics - Wholesale Credit Risk Models & Parameters team, you will play a role in the development, evolution, monitoring, and implementation of credit risk models for wholesale portfolios.

You will lead complex modeling initiatives for different portfolios and geographies, including risk ranking models such as Ratings, Early Warning Systems (EWS), and other decision-support tools, as well as credit risk parameter models—Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD)—under IRB, IFRS9, and Economic Capital frameworks.

The position combines solid quantitative and technical expertise with end-to-end responsibility for projects, the coordination of multidisciplinary teams and stakeholders, and the contribution to the definition and implementation of global methodologies and standards.

You will work closely with area management, local Risk teams, Model Risk Management, Internal Validation, Data & Engineering, Regulatory Affairs, and other relevant stakeholders, ensuring that wholesale credit risk models are robust, efficient, comply with regulatory requirements, and are aligned with BBVA's global analytics strategy.

• Lead the development, backtesting, recalibration, and maintenance of wholesale credit risk models, including ranking models such as Ratings, EWS, and other analytical decision tools, as well as PD, LGD, and EAD models under IRB, IFRS9, and Economic Capital frameworks.
• Assume end-to-end responsibility for complex modeling projects, from initial methodological design and data exploration to the development, documentation, validation, implementation, and monitoring of the model, as well as the resolution of identified limitations.
• Coordinate global credit risk modeling initiatives across different geographies and portfolios, working closely with Holding and local teams to ensure methodological consistency, compliance with deadlines, and adequate implementation in risk management processes.
• Contribute to the definition and continuous evolution of global methodologies, standards, and best practices for the development, monitoring, and backtesting of wholesale credit risk models.
• Ensure compliance with regulatory requirements and supervisory expectations applicable to the models, including IRB, IFRS9, CRR3, EBA guidelines, ECB expectations, ICAAP, and other relevant regulatory frameworks.
• Actively participate in regulatory and supervisory processes related to wholesale credit risk models, preparing technical analyses, documentation, responses, and remediation plans, and participating in interactions with Internal Validation, Model Risk Management, Audit, and supervisory bodies when necessary.
• Proactively identify and evaluate model risks, methodological limitations, data quality issues, and implementation gaps, defining and coordinating the necessary remediation actions with the corresponding stakeholders.
• Perform and review advanced quantitative analyses, including statistical modeling, Machine Learning techniques, evaluation of predictive power and model performance, benchmarking, sensitivity analysis, and other analyses necessary to ensure robust risk methodologies.
• Drive the adoption of advanced analytics and Artificial Intelligence techniques when they allow for improved performance, efficiency, interpretability, or decision-making capacity of the models, ensuring their use in accordance with regulatory requirements and model risk management.
• Collaborate closely with Data & Engineering teams to improve the availability, quality, and traceability of data and the infrastructure that supports the development, monitoring, and implementation of wholesale credit risk models.
• Contribute to the modernization and automation of the model lifecycle, including the evolution from legacy analytical environments toward cloud, scalable, reproducible, and automated platforms for model development and monitoring.
• Provide leadership and technical guidance to data scientists and other team members, reviewing analytical work, questioning and enriching methodological decisions, sharing best practices, and supporting the professional development of less experienced profiles.
• Coordinate multidisciplinary project teams when necessary, establishing work plans, priorities, deliverables, and schedules, and ensuring high-quality execution of different initiatives in parallel.
• Communicate complex quantitative and regulatory issues clearly to senior stakeholders, translating analytical results into conclusions and recommendations that facilitate risk management decision-making.
• Collaborate with other GRM teams, both at Holding and in the geographies, to ensure the proper integration of models and analytical methodologies into BBVA's general risk governance and management frameworks.
• Stay up to date on regulatory developments, market practices, academic research, and technological advances relevant to wholesale credit risk modeling, identifying opportunities to continuously strengthen BBVA's analytical methodologies and capabilities.

Client Orientation, Empathy, Ethics, Innovation, Proactive Thinking