As a Medior Data Scientist, you will deliver production-ready ML and LLM solutions that impact thousands of users and support 8,000 engineers across Rabobank.

You & your role

Design scalable, reliable, and responsible ML and LLM solutions that are tightly linked to engineering workflows. As a Medior Data Scientist, you will navigate ambiguity, adapt to shifting priorities, and persist through complexity. Your work will directly shape how Rabobank teams make decisions and deliver AI-driven experiences safely, at scale, every day.

Examples from practice

• Design end-to-end pipelines for scalable RAG-powered assistants, supporting 8,000 engineers across the organisation.
• Build reusable patterns for ML services and retrieval, incorporating Databricks, vector databases, and modern evaluation and monitoring tools.
• Mentor squads on robust ML and LLM workflows, including clustering, feature engineering, CI/CD, telemetry, and Responsible AI guardrails.

Facts & figures

• 36 or 40 hours per week.
• Work with datasets of millions of records and models that process thousands of queries daily.
• Over 49,000 Rabobank colleagues worldwide.

Top 3 responsibilities

• Design and maintain ML models and LLM/RAG applications, from discovery and prototyping to production-grade delivery, ensuring high-quality features and context optimisation.
• Drive adoption of MLOps/DevOps practices for scalability, resilience, and observability, including Git, CI/CD, monitoring, and alerting across ML/LLM workloads
• Ensure security, compliance, and Responsible AI in all solutions, actively managing model drift, retrieval quality, and prompt robustness.

As Data Scientist, you will be pivotal in delivering secure, scalable, and responsible AI solutions used across Rabobank.

Together we achieve more than alone

We believe in the power of differences. It is precisely by combining people’s differences that we become an even better bank. We are curious about what you add to our team of Analytics Acceleration.

The 25 people of Analytics Acceleration design, build, and operationalise AI solutions that make Rabobank smarter and more customer focused. Collaboration is our approach; as one data minded team within Rabobank, we drive innovation and sustainable performance.

Work on yourself and the world around you at the same time

At Rabobank, your development and that of society go hand in hand. That is why we invest in you and work together for a better world. You will see this reflected in your personal development budget, hybrid working environment, and a healthy work-life balance. You will work on banking for our customers and societal issues such as food and energy transitions.

Why everyone is welcome at Rabobank

At Rabobank, we believe we become stronger through people who complement each other. By embracing our differences, we bring out the best in one another. We seek diversity in areas such as knowledge, skills, and experience, but also in gender, background, and culture. Across every department, we strive for variety and the freedom to be yourself, whoever you are. That is what diversity and inclusion at Rabobank is all about.

You & your talent

• You have worked with data and analytics governance platforms from vendors like Collibra, Informatica, OneTrust, Databricks, and/or Microsoft.
• You have experience in data governance, data protection and/or AI governance.
• You have experience with Graph data platforms and the concept of knowledge graphs
• You know how to define requirements and proof points for the execution of a proof of concept and are also able to document the results.
• You've worked with Azure, provisioning resources using ARM templates, Bicep, PowerShell or the Azure CLI. 
• You have experience working with pipelines-as-code and infra-as-code as well as with Azure DevOps.
• You’re reasonably skilled using Python programming language

Apply

To ensure that we assess all candidates equally for suitability for this position, we do not require a mandatory cover letter. Instead, we ask all candidates the same three questions to see how your profile matches the role. Please pay sufficient attention to answering these questions and explaining your answers. together with your CV, these responses form the basis for our evaluation in this round. Submitting both a CV and answers to the three questions is the minimum requirement to be considered in the selection process. A cover letter is not mandatory but may be submitted optionally.

You may draw on your work experience, volunteer work, education, private life, and so on. Use a maximum of 200 words per question and provide no more than two examples. Below are the questions:

1. Describe a time you improved the scalability or reliability of an ML pipeline.

• What challenges did you face, and how did you apply MLOps principles (CI/CD, monitoring, alerting)?
• Which tools or frameworks did you leverage (e.g., Azure DevOps, Databricks)?
  

2. Give an example of working with ambiguity in a data governance or AI governance context.

• How did you clarify requirements and align stakeholders?
• What was the outcome, and what did you learn?
  

3. Describe a time you worked with knowledge graphs or graph data platforms.

• What was the use case, and how did you design or query the graph?
• How did this enhance retrieval or context optimization for ML/LLM models?

Please submit these answers in the application section titled 'Add your cover letter (optional)' on the website portal.

You & the application process

• Any questions about working at Rabobank and the process? Ashley Lumbantobing, IT Recruiter, ashley.lumbantobing@rabobank.nl
• We will hold the interviews through a video call. If you are selected for an interview, Bo, our virtual assistant, will reach out to you via SMS and email to schedule the interview.
• You can find answers to the most frequently asked questions on rabobank.jobs/en/faq
• A screening is part of the process.
• We respect your privacy.

To be considered for this position, you must be located in the Netherlands and have the legal right to work in the Netherlands. We are unable to consider candidates requiring relocation from another country.

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