Data Scientist Commercial Banking - Associate II

Job description

Excited to grow your career? 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. Learn more about the area: 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). About the job: 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. Skills: Client Orientation, Empathy, Ethics, Innovation, Proactive Thinking