Level

Santander

Senior Data Scientist - AI Evaluation & Product

Santander is hiring a Senior Data Scientist - AI Evaluation & Product. Level rates it ; you can apply on Level.

Level's read on this job

  • Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
  • Tools and skills the posting cites include RAG and AI evaluation.
  • Level files it as a senior role.
  • Level lists 1,000+ other open roles at Santander.
  • The role was posted in the last few days.

AI in this role

ragai-evaluation
Senior Data Scientist - AI Evaluation & Product

Country: Spain

IT STARTS HERE

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.


SENIOR / LEAD DATA SCIENTIST - AI EVALUATION & PRODUCT

THE DIFFERENCE YOU MAKE

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.


MAIN RESPONSIBILITIES

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.

WHAT YOU'LL BRING TO THE TABLE

  • 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.

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.

WE VALUE YOUR IMPACT

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.

LOCAL COMPLIANCE 

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. 

WHAT TO DO NEXT?

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

READY TO TAKE THE NEXT STEP ON YOUR JOURNEY?






#LI-FB1

How we rate this

Senior Data Scientist - AI Evaluation & Product at Santander rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI Evaluation

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$170k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide that one model's output is better than another's for a given task?
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: RAG and AI Evaluation. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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