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# Data Analyst - AI & Product Quality

- **Company:** Trenkwalder Personaldienste GmbH
- **Location:** München, Germany
- **Experience:** Experienced
- **Salary:** €58,000.0 - €95,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Database Queries, Python (Programming Language), PostgreSQL, Machine Learning, Operational Databases, Software Product Management, Large Language Models, Pandas, Scikit Learn, Tools for Reporting
- **Published:** July 20, 2026
- **Apply:** https://www.adzuna.de/details/5805148878

## About the Role

* 3+ years of experience in data analysis or applied ML in a product context
 * Strong SQL skills (PostgreSQL) and experience working with production data models
 * Basic understanding of ML concepts: scoring, ranking, embeddings, LLM evaluation
 * Python skills for data analysis (pandas, scikit-learn, etc.)
 * Ability to communicate findings clearly - to engineers and to management

Nice to have

 * Experience in HR tech, recruiting, or adjacent domains
 * Familiarity with LLM evaluation methods
 * Experience with analytics tools (PostHog, Metabase, etc.)

## Description

* Direct impact on an AI product in daily production use
 * Access to real production data and immediate user feedback
 * Close collaboration with the engineering lead
 * Remote-first, data-driven culture

Ihre Aufgaben

Our platform uses AI for complex tasks: automated matching, profile analysis, anomaly detection. We know the algorithms work - but we want to understand how well, and where they can improve. That's where you come in.

 * Analyze the quality of our core AI-powered features: where do the algorithms perform well, and where are there systematic weaknesses?
 * Build metrics and dashboards to measure platform quality (conversion, adoption, deviation analysis)
 * Evaluate user behavior: how do users interact with AI-generated recommendations?
 * Propose data-driven improvements for existing algorithms - evidence-based, not intuition-based
 * Build evaluation frameworks for AI outputs (structured scoring, comparison runs)
 * Work closely with the engineering team to turn insights into improvements


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