Data Scientist

Promptwatch; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Job summary

Promptwatch, Amsterdam-based, is seeking a data scientist to turn AI responses, citations, and crawler logs into actionable insights. You will build models, metrics, and analyses to measure and optimize brand visibility in AI search.

You will work with large, unstructured data, apply vector search techniques, and present findings clearly to both technical and non-technical stakeholders. This role requires strong Python/SQL skills and a keen interest in AI-driven analytics.

Qualifications

• 4+ years experience in data science, analytics, or a quantitative research role.
• Strong proficiency in Python and SQL for data analysis.
• Solid foundation in statistics, experimentation, and ML fundamentals.
• Experience working with large, messy, real-world datasets, including high volumes of unstructured text.
• Hands-on experience with vector search and embeddings.
• Ability to translate ambiguous questions into clear, measurable analyses.
• Strong communication skills to present findings to technical and non-technical audiences.
• Curious and excited about AI, search, and emerging buyer behavior.
• Familiarity with data warehouses and analytics tooling (e.g. BigQuery, Tinybird/ClickHouse, Elasticsearch)

Skills

Data science

Analytics

Quantitative research

Python

SQL

Statistics

Experimentation

ML fundamentals

Unstructured data

Vector search

Embeddings

AI and search

Communication

Tools

BigQuery

Tinybird

ClickHouse

Elasticsearch

Job description

Turn billions of AI responses, citations, and crawler logs into the insights that power Promptwatch. You'll build the models, metrics, and analyses that define how brand visibility in AI Search is measured and optimized.

• 4+ years experience in data science, analytics, or a quantitative research role;
• Strong proficiency in Python and SQL for data analysis;
• Solid foundation in statistics, experimentation, and ML fundamentals;
• Experience working with large, messy, real-world datasets, including high volumes of unstructured text;
• Hands-on experience with vector search and embeddings;
• Ability to translate ambiguous questions into clear, measurable analyses;
• Strong communication skills to present findings to technical and non-technical audiences;
• Curious and excited about AI, search, and emerging buyer behavior;
• Familiarity with data warehouses and analytics tooling (e.g. BigQuery, Tinybird/ClickHouse, Elasticsearch)