Data Scientist Commercial Banking - Associate II

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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.

Conoce más sobre el área:

At BBVA we believe that Data is a main asset for achieving market differentiation. Commercial Banking Analytics is in charge of delivering value to the business units by participating in strategic projects that have a strong data component, or by creating actionable insights for optimizing the decision making processes at all levels of the Organization. Commercial Banking is a Global unit based in Madrid and interacts with other global departments and with local units all across BBVA’s footprint (Spain, Mexico, South America and Turkey).

Sobre el puesto

Key responsibilities

• Collaborate with key internal and external stakeholders to gather and understand needs and requirements.

• Develop clean, simple and creative code to manipulate large datasets.

• Design and implement robust analytic solutions ranging from basic statistical analysis to advanced machine learning / artificial intelligence models to cover the identified needs.

• Represent / visualize results in the most appropriate format and present your findings effectively to analytical and non-analytical audiences.

• Collaborate with IT teams to convert analytical proof of concepts into productive models.

• Contribute to the exploration and prototyping of Generative AI solutions, including RAG and agentic approaches, when appropriate for the business problem.

Required Skills and Experience

• Solid foundations in areas like:

  • Statistical analysis is a MUST

  • Machine learning for classification, regression and unsupervised tasks is a MUST (actual experience required). Reinforcement learning is a plus

  • Knowledge of classical data science techniques (e.g. time series, NLP, graph analysis, optimization, signal and image processing) is a plus

  • Experience prompting, fine-tuning, and evaluating LLMs is a plus

  • Familiarity with Generative AI concepts and architectures, including RAG, AI agents, agentic workflows and Model Context Protocol (MCP), is a plus

  • Experience with or exposure to cloud-based Generative AI platforms and tools, particularly AWS Bedrock, is a plus

• Programming experience:

  • Excellent programming skills and experience developing production-quality software. 

  • Experience with SQL, Python, PySpark (at least, two of them).

  • Real experience in designing and implementing analytical solutions with different  programming libraries.

  • Knowledge of relevant data science tools and frameworks, including visualization and deep learning libraries.

  • Experience with tools and platforms for building and integrating LLM- and agent-based applications, including cloud services such as AWS Bedrock.

• Business sense to put data in perspective, and extract meaningful conclusions.

• Ability to translate academic results from scientific papers into actionable solutions.

• Experience and knowledge of the financial industry.

• Natural inclination for sharing findings and engaging in problem-solving with teammates, helping them with their challenges, and asking for their help when needed.

• Advanced level of English and Spanish.

• 3+ years of professional experience (data scientist, business intelligence, consulting…).

Preferred Qualifications

• MSc/ PhD in a relevant field such as Statistics, Computer Science, Applied Math, or other related subject.

• Working knowledge of the financial industry products/services and operations.

• Proficiency in Spanish and English.

Habilidades:

Empatía, Ética, Innovación, Orientación al cliente, Pensamiento proactivo