Applied Data Scientist

Job description

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 4 days per week in-office. What you'll do • 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. What we require • 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.