Applied Data Scientist

Draup is a Series A-funded agentic AI company building the intelligence layer for how global enterprises make workforce and go-to-market decisions. We work with 250+ enterprise clients — including 5 of the Fortune 10 — processing 1B+ job descriptions, 850M+ professional profiles, and signals from 100+ labor databases.

 

We are now building our Silicon Valley engineering team — a small, senior group focused on next-generation AI research and product.

 

Location: San Francisco, SoMa: minimum 3 days in-office per week, 2 days flexible.

 

 

• Build and maintain ML models for classification, extraction, trend detection, and predictive scoring on large structured and unstructured datasets.

• Design experiments and benchmarks to measure model accuracy, reduce bias, and validate outputs at scale.

• Apply NLP techniques — embeddings, NER, text classification — to real-world data pipelines.

• Partner with engineering to move models from experimentation to production; own monitoring and drift detection.

• Build evaluation frameworks for AI-generated outputs across multiple product use cases.

 

 

• BS/MS in Statistics, Computer Science, Applied Mathematics, or a quantitative field.

• 3–5 years of applied data science; minimum 2 years working with NLP or large-scale text data in production.

• Strong Python (pandas, scikit-learn, PyTorch or TensorFlow); proficient in SQL.

• Demonstrated track record of shipping models into production, not just producing analysis.

• Experience with embedding models and semantic similarity at enterprise scale.

• No visa sponsorship. Must be authorized to work in the US without current or future employer sponsorship.