Senior Data Scientist - AI Evaluation & Product

Description

The company is a bank building its AI transformation, and its Data & AI Science team (DAISci) is the scientific core of that work.

DAISci develops, evaluates, validates and turns advanced data science and AI methods into robust, production-ready products that create measurable value across the organization.

The role sits in the global AI Transformation team and leads strategic AI initiatives across global companies and key functions, connecting business, AI and technology so that AI solutions deliver measurable value.

You will help define the methods, analytical capabilities and products that let teams assess, understand and improve AI systems and make better evidence-based decisions.

The job title is Senior or Lead Data Scientist, AI Evaluation and Product.

Responsibilities

• Take ownership of data science initiatives from problem framing and prioritization through experimentation, implementation, deployment and ongoing improvement.
• Design methods, metrics, benchmarks and test strategies that assess the quality, performance, reliability and behavior of AI systems.
• Use statistics, experimentation, machine learning and advanced analytics to solve complex, real-world problems.
• Turn business and user needs into clear analytical problems, technical requirements and scalable solutions.
• Work closely with Product, Engineering, Research, Validation and business teams to set priorities, roadmaps and delivery plans.
• Build high-quality analytical assets, prototypes and production-oriented capabilities using sound software engineering and data science practice.
• Use data and evidence to produce actionable insights, support decisions and find chances to improve products and systems.
• Drive technical quality, reproducibility, testing, documentation and maintainability across data science work.
• Handle uncertainty, weigh trade-offs and remove blockers to keep initiatives moving.
• Mentor colleagues and give technical guidance that builds scientific rigor, collaboration and continuous learning.

Requirements

• Master's 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 settings.
• Deep grounding in statistics, experimentation, model evaluation and machine learning.
• Advanced Python skills and solid experience with the modern data science ecosystem, data analysis libraries and machine learning frameworks.
• Ability to structure ambiguous problems, form sound hypotheses and choose suitable analytical or modelling approaches.
• A record of driving complex work independently from initial definition to tangible results.
• Broad experience across the data science lifecycle, from analysis and prototyping to industrialization and monitoring.
• A product mindset that balances technical depth, user needs, delivery constraints and measurable business value.
• Experience working effectively with technical and non-technical stakeholders in dynamic, cross-functional teams.
• Clear communication, able to explain complex concepts, assumptions, limitations and recommendations to different audiences.
• Pragmatic technical leadership that guides decisions, raises quality standards and develops other team members.
• Experience building, 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 heavily governed environments, such as financial services.
• Publications, patents, open-source contributions or other evidence of scientific curiosity and continuous learning.

Conditions

Based in Spain.

Hybrid work: some days remote and some days in person with your team, with flexible schedules.

Shuttle service from several points in Madrid is available.

The company is committed to equal opportunities regardless of age, gender, disability, marital status, race, religion or sexual orientation, and to an accessible application process.

Benefits

• A very competitive salary with performance-based bonuses.
• A fair and competitive rewards package that reflects the impact you make.
• Access to hundreds of courses, including the company's global learning platform.
• Preferential banking terms, special interest rates on loans and life insurance.
• BeHealthy, a global wellness program that supports holistic health.
• Child care support and family programs for every stage of life.
• An employee and family support program offering legal, emotional and administrative advice.
• Gym or WellHub membership, medical centers at some sites, meal allowance, parking, and discounts and exclusive offers for employees.
• Access to global opportunities and broad career paths.