Senior Data Scientist - AI Evaluation & Product

Location: Boadilla del Monte, Spain; hybrid work with some days remote and some days in person with the team.

Company

Santander is a global bank undergoing a technology-driven transformation through Data Science and AI.

What you will do

• Lead Data Science initiatives end to end, from problem framing and prioritization through experimentation, implementation, deployment, and continuous improvement.
• Design methodologies, metrics, benchmarks, and testing strategies to evaluate the quality, performance, reliability, and behavior of AI systems.
• Apply statistical analysis, experimentation, machine learning, and advanced analytics to complex real-world problems.
• Translate business and user needs into analytical problems, technical requirements, prototypes, and scalable production-oriented solutions.
• Partner with Product, Engineering, Research, Validation, and Business teams on priorities, roadmaps, and delivery plans.
• Ensure technical quality, reproducibility, testing, documentation, and maintainability while mentoring colleagues and providing technical guidance.

Requirements

• MSc or PhD in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or another related quantitative field.
• Experience evaluating AI systems, machine learning models, or intelligent applications through benchmarking, experimentation, or quality-assessment frameworks.
• Knowledge of Generative AI, large language models, conversational systems, retrieval-augmented generation, or agent-based systems.
• Strong professional experience delivering Data Science or Machine Learning solutions in complex, real-world environments.
• Deep foundations in statistics, experimentation, model evaluation, and machine learning, with advanced Python programming skills and strong experience with the modern Data Science ecosystem, data analysis libraries, and machine learning frameworks.
• Ability to structure ambiguous problems, form hypotheses, select analytical or modelling approaches, and independently drive complex work to tangible outcomes.
• Broad experience across the Data Science lifecycle, from analysis and prototyping to industrialization and monitoring.
• Product mindset balancing technical depth, user needs, delivery constraints, and measurable business value.
• Experience working with technical and non-technical stakeholders, communicating complex concepts clearly, and providing pragmatic technical leadership.

Nice to have

• Experience developing, deploying, or maintaining production-grade Data Science or Machine Learning systems.
• Experience contributing to product strategy, roadmap definition, discovery, or prioritization in a product-led environment.
• Experience leading technical workstreams or mentoring Data Scientists and other technical professionals.
• Experience in regulated or highly governed environments, such as financial services.
• Publications, patents, open-source contributions, or other evidence of scientific curiosity and continuous learning.

Culture & Benefits

• Hybrid work model with flexible schedules and global career opportunities.
• Access to hundreds of courses and Santander Open Academy.
• Competitive salary with performance-based bonuses.
• Preferential banking terms, special loan interest rates, life insurance, wellness support, and family programs.
• Additional benefits may include gym or WellHub membership, medical centers, meal allowance, parking, shuttle service from Madrid, and employee discounts.

Hiring process

• Submit an application for consideration.