Data Scientist -GenAI

SageBeans RPO; Utrecht; On-site; EUR 70,000 - 100,000; Full time

Job summary

SageBeans RPO is seeking a Data Scientist specialising in GenAI and chatbot optimisation in Utrecht. You will work at the intersection of data science, engineering, and product development to improve AI-powered chatbots, focusing on behaviour understanding, performance gaps, and practical improvements.

You will assess existing solutions against GenAI best practices, enhancing retrieval, generation, reasoning loops, tool calling, and related capabilities to deliver measurable improvements in

Qualifications

• Strong understanding of Generative AI systems and their practical applications.
• Hands-on experience developing, evaluating, or optimising LLM-based applications.
• Experience with Retrieval-Augmented Generation (RAG) systems.
• Strong understanding of prompt engineering, context windows, retrieval strategies, and grounding.
• Ability to analyse AI-generated responses and identify the underlying causes of poor performance.

Responsibilities

• Analyse chatbot outputs and identify improvements with the greatest impact.
• Diagnose context gaps and determine information AI agents require to perform effectively.
• Collaborate with product managers and engineers to establish evaluation criteria for agent performance.
• Work with business use-case teams to translate feedback into technical improvements.
• Improve retrieval mechanisms, data structuring, and contextual data onboarding.
• Design evaluation frameworks for rapid experimentation, large-scale testing, and continuous improvement.
• Translate requirements into actionable technical solutions.
• Evaluate chatbot responses to understand what makes outputs effective or not.
• Assess existing implementations against GenAI best practices and identify opportunities for innovation.
• Troubleshoot data flows, context ingestion, and integration issues affecting chatbot performance.

Skills

GenAI

LLM Expertise

RAG techniques

Prompt engineering

Job description

Role Overview We are looking for a Data Scientist specialising in GenAI and Chatbot optimisation. In this role, you will work at the intersection of data science, engineering, and product development to improve the quality, accuracy, and effectiveness of AI-powered chatbot systems. Rather than developing foundation models, your primary focus will be on understanding chatbot behaviour, identifying performance gaps, and translating your findings into practical improvements. You will investigate questions such as:

• Why is the chatbot not delivering the expected results?
• Is the issue related to missing context, retrieval quality, prompt design, or data structure?
• What additional information does the AI assistant need to produce better responses?
• How can chatbot performance be evaluated and improved systematically?

You will assess existing solutions against state-of-the-art GenAI approaches and drive improvements across retrieval, generation, reasoning loops, tool calling, and other relevant GenAI capabilities. This is an ideal opportunity for a technically strong, analytical professional who enjoys debugging AI behaviour and making AI applications work more effectively in real-world scenarios.

Responsibilities

• Analyse chatbot outputs and identify the improvements that will have the greatest impact.
• Diagnose context gaps and determine what additional information AI agents require to perform effectively.
• Collaborate with product managers and engineers to establish evaluation criteria for agent performance.
• Work closely with business use-case teams and stakeholders to understand real-world requirements and translate feedback into technical improvements.
• Improve retrieval mechanisms, data structuring, and the onboarding of contextual data sources.
• Design evaluation frameworks that support rapid experimentation, large-scale testing, and continuous improvement.
• Translate functional and business requirements into actionable technical solutions.
• Evaluate chatbot responses to understand why particular outputs are effective or ineffective.
• Assess existing implementations against current GenAI best practices and identify opportunities for innovation.
• Troubleshoot data flows, context ingestion, and integration issues affecting chatbot performance.

Required Skills

Essential Skills and Experience GenAI and LLM Expertise

• Strong understanding of Generative AI systems and their practical applications.
• Hands-on experience developing, evaluating, or optimising LLM-based applications.
• Experience with Retrieval-Augmented Generation (RAG) systems.
• Strong understanding of prompt engineering, context windows, retrieval strategies, and grounding.
• Ability to analyse AI-generated responses and identify the underlying causes of poor performance.