Applied Data Scientist

· 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.