Data Scientist

Details

Turn billions of AI responses, citations, and crawler logs into the insights that power Promptwatch. You will build the models, metrics, and analyses used to measure and optimize brand visibility in AI Search.

Promptwatch works with AI responses from ChatGPT, Claude, Gemini, and Perplexity, together with billions of crawler logs and clicks. The platform processes approximately 2,000 events per second from crawler logs, CDN data, and clickstream data, alongside large volumes of unstructured AI response text.

Responsibilities

• Design and refine metrics for brand visibility, citations, and sentiment across AI assistants.
• Analyze large-scale, high-velocity datasets, including crawler logs, CDN data, and clickstream data, to identify actionable trends.
• Analyze unstructured AI response text using embeddings and vector search.
• Build statistical and machine learning models to detect patterns in how AI systems retrieve, rank, and cite content.
• Develop reproducible analyses and pipelines that scale with the growing dataset.
• Produce public-facing research and reports on the AI search space.
• Validate data quality and define methodologies that customers can trust.
• Work closely with Product and Engineering to develop visibility and sentiment metrics, identify trends across millions of AI answers, and build the analytical foundation for customer insights and public research.

Requirements

• 4+ years of 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 machine learning 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 for presenting findings to technical and non-technical audiences.
• Curiosity and enthusiasm for AI, search, and emerging buyer behavior.
• Familiarity with data warehouses and analytics tooling such as BigQuery, Tinybird/ClickHouse, and Elasticsearch.

Nice To Have

• Experience with natural language processing or working with large language model outputs.
• Background in SEO, search, or marketing analytics.
• Experience building data visualizations or dashboards.

Benefits

• Great office location.
• Team off-sites.
• Company and team sports activities.