Senior Data Scientist, AI Evaluation & Product — Hybrid

Banco Santander SA; Santa Bàrbara; Hybrid; EUR 80,000 - 110,000; Full time

Benefits offered by this job

Gym/WellHub membership

Meal allowance

Parking

Shuttle service Madrid

Job summary

Santander DAISci is seeking a Senior Data Scientist to lead and oversee AI evaluation and product-oriented analytics. You will drive end-to-end frameworks, build scalable evaluation methods, and collaborate with product, engineering, and research teams to translate business needs into measurable AI outcomes.

You will advance statistical modeling, experimentation, and robust production-ready analytics, while mentoring colleagues and fostering a culture of scientific rigor and continuous learning

Qualifications

• MSc or PhD in a quantitative field such as CS, AI, or data science.
• Experience evaluating AI systems through benchmarking and experiments.
• Knowledge of Generative AI and large language models.
• Strong programming in Python and ML frameworks.

Responsibilities

• Lead end-to-end design of analytical frameworks for evaluating AI systems.
• Define methodologies, metrics, and testing strategies.
• Collaborate with Product, Engineering, Research, Validation, and Business teams to shape priorities.
• Mentor colleagues and drive scientific rigor across Data Science efforts.

Skills

Statistics

Experimentation

Model evaluation

Machine learning

Python

Data analysis libraries

Education

MSc or PhD in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering

Tools

Python libraries

ML frameworks

Job description

Santander DAISci is seeking a Senior Data Scientist to lead and oversee AI evaluation and product-oriented analytics. You will drive end-to-end frameworks, build scalable evaluation methods, and collaborate with product, engineering, and research teams to translate business needs into measurable AI outcomes.

You will advance statistical modeling, experimentation, and robust production-ready analytics, while mentoring colleagues and fostering a culture of scientific rigor and continuous learning