Data Scientist -GenAI / Chatbot

Important:

• We are looking for 1 FTE.
• We will close the vacancy before the indicated deadline when we have received enough professionals.
• Please clearly indicate in the motivation field whether the candidate has any planned vacation or special leave during the duration of this assignment.
• Please provide in the CV whether an internal reference can be requested. If the candidate is currently working at, or has recently worked at, Rabobank, we would appreciate receiving the name and job title of the relevant team lead.
• Language: English
• ZZP Allowed: No.

Hybrid working: Thursday in office (Location Winthontlaan, Utrecht until further notice).
Level: Medior–Senior.

Application process details:
The process consists of an initial one-hour interview with two of our Data Scientists to assess your technical skills, followed by a 30-minute conversation with the team manager to evaluate team fit.

As Data Scientist (GenAI / Chatbot), you know the secrets of making AI assistants perform at their best.

You will work at the intersection of data, engineering, and product thinking, helping to improve the quality and effectiveness of chatbot systems. Rather than building foundation models, your focus will be on understanding chatbot behaviour, identifying weaknesses, and translating insights into meaningful improvements.

You help answer a fundamental question:
“Why is this chatbot not doing what we expect, and what context or structure does it need?”

You will assess current solutions against state-of-the-art approaches and drive innovation across retrieval, generation, reasoning loops, tool calling, and related GenAI capabilities.

Your Responsibilities:

• Analyse chatbot outputs and identify the improvements with the greatest impact;
• Diagnose context gaps and determine what additional information agents require;
• Partner with product managers and engineers to define evaluation criteria for agent performance;
• Work directly with use-case teams and stakeholders to understand real-world scenarios and translate feedback into improvements;
• Improve retrieval mechanisms, data structuring, and onboarding of contextual sources;
• Design evaluation frameworks that enable rapid, large-scale experimentation and continuous innovation;
• Translate functional requirements into actionable technical improvements.

Your Talent:

• You bring a strong analytical mindset and a passion for understanding why AI systems behave the way they do;
• Strong understanding of GenAI systems;
• Experience with LLM-based applications;
• Experience with retrieval-augmented systems;
• Strong understanding of prompts, context windows, retrieval, and grounding;
• Ability to evaluate output quality and explain why results are effective or ineffective.

Technical Integration Skills:

• Familiarity with API integrations, batch synchronisation, and structured and unstructured data;
• Comfortable collaborating closely with engineers;
• Ability to troubleshoot data flow and context ingestion issues.

Analytical and Evaluative Mindset:

• Ability to design evaluation frameworks beyond traditional machine learning metrics;
• Understanding of functional context and user behaviour;
• Ability to operate effectively between engineering and product domains.

Clear Communicator:

• Ability to explain context gaps and reasoning to engineers, product managers, and stakeholders;
• Ability to create clear and effective improvement proposals.

Nice to Have:

Background in human-in-the-loop evaluation.

Who Will Thrive Here: This role is ideal for someone who enjoys understanding why AI systems behave the way they do and how they can be improved.

… lees de volledige omschrijving bij De Publieke Partner.