Data Scientist
Kaizo · 🇳🇱 Amsterdam, Netherlands
Sponsorship Verification Proof
The posting itself mentions visa sponsorship or relocation support:
“• Enjoy the perks: flexible hours, open holiday policy, an office in the heart of Amsterdam with hybrid flexibility, visa sponsorship, great gear, workations, and team events.”
- Verification category
- Posting mentions visa sponsorship / support
- Role category
- Data
- Last verified
- 2026-10-25
- First indexed
- 2026-10-24
- Posted date
- 2026-10-22
- ATS / Feed source
- Arbeitnow
Role Description (Excerpt)
Do you want to work out how you actually measure whether an AI system is doing a good job, and then make it better? We're looking for a sharp, analytical data scientist to own the evaluation and quality loop of our AutoQA product. You can be early in your career (recent graduates with strong LLM fundamentals are welcome), we have room and a clear path for you to grow. In a nutshell • Join a fast-growing SaaS company in an international environment (steep learning curve guaranteed). • Own a high-impact problem: making LLM-powered quality assurance measurably accurate at scale. • Sit at the intersection of AI and CX, working directly with enterprise customers and their real-world QA rubrics. • Grow into a Senior Data Scientist, AI Engineer, or ML Engineer role. We invest in progression. • Enjoy the perks: flexible hours, open holiday policy, an office in the heart of Amsterdam with hybrid flexibility, visa sponsorship, great gear, workations, and team events. About Kaizo At Kaizo, we build a performance development and quality platform for customer support teams. Our AutoQA product uses LLMs to review support conversations against each customer's own quality rubric, automatically and at scale. Behind it sits a microservices-based stream processing platform handling over 200 million events per day (Kafka, Kubernetes on Google Cloud, ElasticSearch, MongoDB, BigQuery), and an LLMOps stack built around LangSmith for experimentation, prompt management, and tracing. The hard part…
Excerpt only — read the full requirements and apply directly on Kaizo's career page. Listing data via Arbeitnow. We do not process applications.