Senior Data Scientist

We are looking for an end-to-end Data Scientist to design, build, and maintain ML-powered systems that solve core data quality and classification problems across the business. You will own the full lifecycle — from exploratory analysis and feature engineering through model training, deployment, and ongoing performance monitoring. The work spans entity resolution ( identifying duplicate records across large datasets) and multi-class classification models that drive decision-making across a variety of business domains.

What You'll Do

Own the end-to-end model lifecycle: problem framing, data exploration, feature engineering, model training, evaluation, deployment, and monitoring • Build and maintain entity resolution systems that detect duplicate records using supervised ML and string similarity techniques • Develop classification models that categorize unstructured or semi-structured data into meaningful business categories • Engineer features from messy, real-world text data — names, addresses, free-text fields — using string matching algorithms, phonetic encoding, n-grams, and other NLP techniques • Design candidate retrieval and indexing strategies to make models performant at scale • Tune thresholds, scoring logic, and rule-based overrides to balance precision and recall for production use cases • Maintain production model artifacts and data pipelines, ensuring models stay current as underlying data evolves • Collaborate with engineering and product teams to understand

and translate business problems into well-scoped modeling tasks