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BBVA es una compañía global con más de 160 años de historia que opera en más de 25 países donde damos servicio a más de 80 millones de clientes. Somos más de 121.000 profesionales trabajando en equipos multidisciplinares con perfiles tan diversos como financieros, expertos legales, científicos de datos, desarrolladores, ingenieros y diseñadores.
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Publicación activa hasta el 15 de Octubre*
The Global Risk Management (GRM) division plays a crucial role in ensuring sustainable growth and value creation through risk-adjusted profitability strategies.
Our mission is to enhance capital efficiency and strengthen risk management by leveraging data, advanced analytics, artificial intelligence and digitization frameworks.
Sobre el puesto
As Senior Manager for Retail Credit Risk Models & Parameters, you will focus on overseeing and contributing to the development, monitoring, and enhancement of credit risk rank ordering models (Scoring and Rating for origination, customer management, and collections, income estimation, etc.) for Retail portfolios. This role requires strong expertise in credit risk analytics, data science, and regulatory compliance, with the ability to collaborate closely with a team of data scientists to ensure high-quality, compliant model delivery.
You will join a team of senior data scientists, driving excellence in credit risk model development, regulatory alignment, and advanced analytics. Your work will directly impact BBVA’s risk management strategy, ensuring compliance with BIS, EBA, ECB, CRR3, IFRS9, and other supervisory expectations while optimizing risk-adjusted profitability.
Main Functions
- Support the implementation and execution of the roadmap for Retail credit risk rank ordering models (origination scorecards, behavioural and proactive scorecards, collections models, income estimators, etc.), collaborating with Local and Holding stakeholders to ensure alignment and effective integration within risk management processes.
- Support the definition and application of group-wide standards for the development, monitoring, and backtesting of Retail credit risk rank ordering models, ensuring alignment with market best practices and internal governance requirements.
- Oversee the ongoing development, backtesting, and recalibration of Retail credit risk models, ensuring compliance with BIS, EBA, ECB guidelines, and standards, including CRR3, EBA GLs, ECB EGIM, ICAAP, and IFRS9. Ensure adherence to governance frameworks, documentation requirements, and regulatory expectations.
- Collaborate closely with Data and Engineering teams to identify and resolve data quality and infrastructure issues impacting the quality of the Retail credit risk models.
- Support the identification, assessment, and mitigation of model risks and limitations across the lifecycle of Retail credit risk rank ordering models. Work closely with internal stakeholders, including Model Risk and Internal Validation teams, to address gaps, implement enhancements, and ensure that recommendations and limitations are effectively resolved.
- Contribute to the innovation and enhancement of Retail credit risk models by applying AI and advanced Machine Learning techniques, and by exploring the use of alternative data sources (e.g., credit bureaus, digital footprint, sociodemographic data, customer networks) to improve predictive accuracy and support better decision-making..
- Collaborate in cross-functional initiatives with Advanced Analytics teams (Client Solutions, Engineering, etc.) to identify and leverage additional data sources that can strengthen Retail credit risk rank ordering models.
The selected candidate will report to the Principal Manager for Retail Credit Risk Models & Parameters and will play a key role in the team, contributing to the delivery of high-quality, compliant credit risk models.
Minimun Requirements
- Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Over 10 years of experience in developing, validating, and monitoring Retail credit risk rank ordering models across the entire credit lifecycle—origination, customer management, and recoveries.
- Solid knowledge of regulatory frameworks (IRB, IFRS9), with experience supporting remediation initiatives and ensuring compliance with supervisory requirements.
- Hands-on experience in IRB Roll-out, Return to Compliance (RtC), and EBA Repair Programs and/or IFRS9 model development and validation programs is desirable.
- Experience with Artificial Intelligence, advanced Machine Learning techniques and Cloud-based technologies (AWS) will be considered a strong advantage.
- Strong knowledge of alternative data sources relevant to credit risk modeling, including credit bureaus, digital footprint, client networks, fraud data, open data, and other non-traditional sources, to enhance predictive power and decision-making.
- Strong project management skills, with experience in managing regulatory and analytical initiatives, ensuring timely delivery and compliance with internal and external requirements.
- Excellent communication skills, capable of translating complex technical concepts for diverse stakeholders.
- Fluent in English (written and spoken).
- Willingness to travel as needed to meet business objectives.
Habilidades:
Empatía, Ética, Innovación, Orientación al cliente, Pensamiento proactivo
