Product Data Scientist (AI)

TL;DR

Product Data Scientist (AI): Owning and extending the evaluation loop for AI products with an accent on quality metrics, regression testing, and production feedback loops. Focus on building robust evaluation suites, maintaining quality dashboards, and translating analytical insights into actionable product decisions.

Location: Must be based in Europe (Remote/Hybrid)

Company

hirify.global is a European fintech startup building an all-in-one B2B financial platform that integrates banking, accounting, and invoicing for entrepreneurs.

What you will do

• Own and extend the offline evaluation suite, including datasets, judges, and metrics.
• Build and maintain online quality dashboards to track resolution rates, latency, and error rates.
• Mine failure patterns from real traffic to create regression cases and propose product fixes.
• Harden evaluation methodology, including judge stability and non-determinism handling.
• Translate complex data into clear decisions through weekly syncs and trade-off analysis.

Requirements

• Must be based in Europe
• 3+ years of experience in analyst or data scientist roles, with at least one year in a product context.
• Proficiency in Python and SQL for end-to-end analysis.
• Solid foundation in statistics, including sampling, hypothesis testing, and variance.
• Analytical mindset focused on business questions rather than specific tools.
• Willingness to use AI-assisted coding (Claude Code) as the default authoring environment.

Nice to have

• Experience in quality analytics for ML systems (ranking, recommendations, classification).
• Hands-on experience evaluating LLM applications (RAG, agents, tool use).
• Experience building LLM agents through side projects or experiments.

Culture & Benefits

• Stock Options Program available to all team members.
• Flexible remote or hybrid work model across Europe.
• Work & Swim program: opportunity to spend one month in a corporate apartment in Cyprus.
• Focus on thorough research and swift implementation in a startup environment.
• Commitment to professional development and well-being.