Senior Data Scientist - AI Evaluation & Product

Santander (www.santander.com) is evolving from a high-impact global brand to a technology-driven organization, and our people are at the heart of this journey. Together, we are driving a customer-centric transformation that values bold thinking, innovation, and the courage to challenge what's possible.

This is more than a strategic shift. It's an opportunity for motivated professionals to grow, learn, and make a real difference.

Our mission is to help people and businesses thrive. As part of the global AI Transformation team, you'll lead and manage strategic AI initiatives that drive impact across global companies and key functions. We are looking for someone who connects business, AI, and technology, ensuring that AI solutions create measurable value.

Santander’s Data & AI Science (DAISci) team is the scientific engine of the bank’s AI transformation. We develop, evaluate, validate, and translate advanced Data Science and AI methods into robust products and capabilities that create measurable value across the organization.

DAISci operates at the intersection of scientific depth, product innovation, and real-world delivery. We combine rigorous analysis with pragmatic execution to address complex challenges and build scalable, reliable, and production-ready solutions.

Joining DAISci is an opportunity to work on strategic initiatives that shape how AI systems are assessed, understood, and continuously improved. You will help define evaluation methodologies, analytical capabilities, and products that enable teams to make better evidence-based decisions.

This role will be a key driver of AI evaluation and product excellence, combining technical and scientific depth with versatility, strong ownership, and the ability to move complex initiatives from ambiguity to delivery.

We are seeking a Senior Data Scientist or Lead Data Scientist to drive the design and delivery of analytical frameworks, methodologies, and products focused on the evaluation and continuous improvement of AI systems.

The ideal candidate is a versatile and experienced Data Scientist who combines scientific rigor with a pragmatic product mindset. You will be comfortable going deep into technical problems, working across disciplines, and taking end-to-end responsibility for delivering meaningful outcomes in a dynamic environment.

• →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 solve complex real-world problems.
• →Translate business and user needs into clear analytical problems, technical requirements, and scalable solutions.
• →Partner closely with Product, Engineering, Research, Validation, and Business teams to shape priorities, roadmaps, and delivery plans.
• →Build high-quality analytical assets, prototypes, and production-oriented capabilities using sound software engineering and Data Science practices.
• →Use data and evidence to generate actionable insights, support decisions, and identify opportunities for product and system improvement.
• →Drive technical quality, reproducibility, testing, documentation, and maintainability across Data Science work.
• →Navigate uncertainty, manage trade-offs, and proactively remove blockers to move initiatives forward.
• →Mentor colleagues and provide technical guidance, contributing to a culture of scientific rigor, collaboration, and continuous learning.

• 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 scientific and analytical foundations, including statistics, experimentation, model evaluation, and machine learning.
• Advanced programming skills in Python and strong experience with the modern Data Science ecosystem, data analysis libraries, and machine learning frameworks.
• Ability to explore and structure ambiguous problems, form sound hypotheses, and select appropriate analytical or modelling approaches.
• Demonstrated ownership and accountability, with a track record of independently driving complex work from initial definition to tangible outcomes.
• Broad and versatile experience across different stages of the Data Science lifecycle, from analysis and prototyping to industrialization and monitoring.
• Product mindset, with the ability to balance technical depth, user needs, delivery constraints, and measurable business value.
• Experience working effectively in dynamic, cross-functional environments with technical and non-technical stakeholders.
• Clear communication skills and the ability to explain complex concepts, assumptions, limitations, and recommendations to different audiences.
• Pragmatic technical leadership, including the ability to guide decisions, raise quality standards, and support the development of other team members.

• 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.

Your contribution matters, and it's recognized. You can expect a fair and competitive rewards package that reflects the impact you create and the value you offer. But we know that rewards go beyond numbers.

• We enable our teams to go further through global opportunities and broad career paths.

• Flexibility that works. Enjoy hybrid work models—some days remote, some days in-person with your team—along with flexible schedules.

• Learning for life. Access hundreds of courses on our platforms, including exclusive access to our global learning space: Santander Open Academy (www.santanderopenacademy.com)

• Competitive rewards. Receive a very competitive salary with performance-based bonuses, which motivates you to continue growing with us.

• Economic advantages. Take advantage of preferential banking terms, special interest rates on loans, life insurance, and more.

• Your health is our priority. Through BeHealthy, our global wellness program, we promote  holistic wellness.

• We know that family is everything. That's why we offer child care support and family programs tailored to every stage of life.

• Always by your side. Access Santander Contigo, our program for employees and their families that offers legal, emotional and administrative advice services.

• Extra benefits. Gym/WellHub membership, medical centers in some of our facilities, meal allowance, parking, shuttle service from various points in Madrid, as well as discounts and exclusive offers for Santander employees. And that's just the beginning—we'll tell you more when you join.

We're here to keep you motivated, help you reach your goals, and celebrate your progress every step of the way.

Santander is proud to be an organization where there are equal opportunities regardless of age, gender, disability, marital status, race, religion or sexual orientation. We are committed to providing an inclusive and accessible application process for all candidates. 

If this sounds like a position you're interested in, apply. 
 

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