Senior Data Scientist - Foundation Model - AI Factory

bbva; Madrid; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

BBVA, una empresa global con más de 160 años de historia, busca un Data Scientist Senior para unirse a AI Factory. Diseñará, entrenará y evaluará modelos a gran escala, manejando datos estructurados y no estructurados del sector financiero y colaborando con equipos multidisciplinares.

El rol implica decidir arquitecturas, estrategias de entrenamiento y despliegue, asegurando soluciones fiables, responsables y reutilizables.

Formación

• Data Scientist senior con experiencia en diseño, entrenamiento y evaluación de modelos a gran escala.
• Conocimiento de datos estructurados y no estructurados en entornos financieros.

Responsabilidades

• Diseñar, entrenar y evaluar modelos de Foundation en un contexto de banca.
• Tomar decisiones sobre arquitecturas, objetivos de aprendizaje y despliegue de modelos.
• Trabajar con equipos multidisciplinares para mejorar decisiones técnicas y calidad del proyecto.

Descripción del empleo

¿Te entusiasma hacer crecer tu carrera?

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.

Conoce más sobre el área:

At AI Factory, we're at the forefront of AI and machine learning innovation-building products that seamlessly blend deep technical excellence with unmatched business and user value. Our mission is to accelerate delivery of scalable AI products while fostering a strong product culture, technical excellence, and responsible AI adoption.

As a Senior Data Scientist within the AI Solutions discipline, you will contribute deep technical expertise to the evolution of BBVA's financial foundation model , working across design, pre-training, adaptation, evaluation, and large-scale training infrastructure to help build reliable, responsible, and reusable AI capabilities that can transform how data is understood and applied across the organisation.

Sobre el puesto

BBVA is developing state-of-the-art capabilities designed around the specific characteristics of financial services. As part of this ambition, we are exploring foundation models that can learn from the different forms of information generated across banking, including transactional sequences, product interactions, operational events...

We are looking for a Data Scientist with strong expertise in the design, training, adaptation, and evaluation of large-scale AI models. This is a senior position for someone who can address difficult technical problems, contribute specialist knowledge, and take end-to-end ownership of important areas of the foundation model lifecycle.

The role will contribute to decisions involving model architectures, training objectives, data preparation, distributed training, fine-tuning, evaluation, and production deployment. The successful candidate will work closely with other engineers, researchers, data specialists, platform teams, and business stakeholders, using their expertise to improve technical decisions and raise the overall quality of the initiative.

What Makes This Role Different

This is not a conventional position, it is an opportunity to contribute to the creation of a new AI capability that could influence how data and intelligence are used across BBVA.

The Foundation Models initiative aims to establish general purpose components that can support multiple areas of the organisation. Its potential extends across credit, recommenders, LTV, financial crime, etc.

The initiative could also change how AI solutions are developed within BBVA. Instead of building separate models and data pipelines for every problem, teams may be able to use shared representations and adaptable model capabilities as a common starting point. Your expertise will contribute to choices involving project end-2-end.

Key Responsibilities

• Foundation Model Development

  Define approaches for filtering, sampling, balancing, sequencing, and combining data from different banking domains.

  Design tokenisation, feature representation, masking, and sequence-generation strategies suited to financial information.

  Address the characteristics of sensitive, sparse, imbalanced, and temporally ordered data.

  Detect and mitigate potential issues such as information leakage, historical bias, missing values, geographic variation, and changes in behaviour over time.

  Design, implement, and train models adapted to financial and banking information.

  Contribute expert judgement to the selection of architectures, learning objectives, training strategies, and customer and event representations.

  Work with structured and unstructured sources, including text, tabular datasets, transactions, event sequences.

  Investigate and resolve problems related to convergence, training stability, data quality, memory usage, and computational performance.

  Design reproducible experiments and evaluate technical alternatives using clear evidence and well-defined criteria.

  Develop and compare adaptation strategies, including continued pre-training, supervised fine-tuning, parameter-efficient methods, and task-specific modelling approaches, selecting the most appropriate technique for each financial use case.

• Training Infrastructure and scale

  Work with platform and engineering teams to define, evolve, and use the technical environments required for reliable large-scale model training.

  Improve accelerator utilisation through profiling, parallelism, scheduling, memory optimisation, and performance tuning.

  Monitor long-running experiments and implement mechanisms that improve their reliability, recoverability, and auditability.

  Evaluate model performance across countries, customer groups, products, time periods, and changing economic conditions.

  Support the transition of successful