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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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La vacante estará activa hasta el 3 de julio hasta las 00:00 h.
Global Risk Management (GRM) is dedicated to contributing to the Group’s responsible growth and recurring value creation by implementing a holistic and forward-looking approach to manage all financial risks. Our approach prioritizes sustainability as a lever for growth, promotes the Group's risk culture with the best team, and leverages the capabilities offered by data, advanced analytics, artificial intelligence, and digitalisation.
About the job:
As Principal Manager for Analytics Transformation within GRM Data & Analytics, you will lead the redefinition of how Risk Data Scientists (DSc) operate across the BBVA Group. You will be responsible for designing, standardising, and automating the Ways of Working for the development of AI models, including traditional ML and GenAI models, with a clear focus on accelerating Time to Value (TtV), and driving the adoption of strategic platforms such as GRMLab -our proprietary risk modelling library- AWS cloud-based capabilities and GenAI technologies across the GRM function.
This is a high-impact, highly visible role reporting directly to the Global Head of GRM Data & Analytics and forming part of the leadership team.
Main Functions
Define a roadmap and implement ML and AI capabilities for the DSc in GRM across BBVA Group, covering all aspects of an E2E model development pipeline, including data collection, data cleansing, feature engineering, model training, model testing, model deployment, continuous monitoring, and model retraining/fine-tuning.
Develop and scale strategies to increase productivity through reusable components and templates integrated into efficient AI/ML pipelines.
Lead the evolution of GRMLab, integrating AWS-native capabilities to facilitate scalable, secure, and compliant model development.
Act as the responsible lead within GRM for promoting, enabling, and monitoring the adoption of GenAI tools (e.g. ChatGPT), ensuring their effective use.
Monitor the development and implementation of GenAI use cases across geographies, ensuring timely execution and alignment with strategic objectives.
Identify and evaluate new opportunities to apply GenAI technologies to optimise risk management processes and shape a forward-looking use case pipeline.
Provide expert guidance on FinOps practices to ensure efficient and cost-effective use of cloud resources for analytics workloads in GRM.
Define and track strategic KPIs, including TtV, reusability of analytical components, adoption of GRMLab and AWS, and volume of GenAI use cases across GRM.
Oversee the roll-out of training programmes defined by the Data Analytics Transformation Core Service, ensuring effective delivery in areas such as MLOps, GenAI, and cloud-based analytics.
Act as the central point of contact in GRM for training delivery, participation tracking, and impact assessment, continuously improving the function’s capabilities.
Serve as the key reference in GRM for BBVA’s Advanced Analytics Community of Practice, fostering alignment, knowledge sharing, and adoption of common methodologies.
Collaborate cross-functionally with teams in Risk, Data, and Engineering, across different geographies, to ensure effective implementation of transformation initiatives.
- Master’s degree or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
- 10–15 years of professional experience in Advanced Analytics, Data Science, or Engineering roles, with a solid track record of delivering complex, high-impact projects within large organisations.
- At least 10 years of experience leading diverse, multidisciplinary teams, with
- Minimum of 5 years designing and implementing MLOps pipelines, including
- AWS certification(s) (e.g. AWS Certified Machine Learning – Specialty, AWS Certified Solutions Architect, or equivalent), along with hands-on experience using AWS-native tools for ML and data pipelines — or similar capabilities in other cloud platforms — would be strongly valued.
- Excellent communication and stakeholder management skills, with the ability to convey complex technical ideas clearly and persuasively to both technical and non-technical audiences.
- Fluency in English (written and spoken); additional languages are a plus.
- Strong interpersonal skills, with a collaborative and inclusive mindset; a one-team spirit is essential for success in this role.
- Willingness to travel as needed to support collaboration across countries and teams within the Group.
Skills:
Customer Targeting, Empathy, Ethics, Innovation, Proactive Thinking
