Data Scientist

## About the Role Spade processes and enriches financial transaction data for major financial institutions — including Stripe, FIS, Bilt, Corpay, and Mercury — handling hundreds of billions in monthly transaction volume in under 50ms. As a Data Scientist, you will own ML/AI products end-to-end, building NLP and entity resolution models that transform raw transaction data into enriched financial intelligence. ## Responsibilities - Own ML/AI products end-to-end from problem framing through deployment and iteration - Develop and productionize ML/AI models for merchant entity resolution, transaction enrichment, and data quality improvements - Design and maintain end-to-end data workflows, pipelines, and testing frameworks for production systems - Collaborate with engineering, analytics, and product to translate ambiguous problems into shipped features - Use customer insights and internal metrics to identify opportunities within transaction data - Partner with leadership to define data science strategy, roadmaps, and best practices ## Requirements - 5+ years of industry experience in data science or ML - Deep expertise in ML, statistical modeling, deep learning, and entity resolution - Fluency in Python (ML/statistical libraries) and SQL - Experience in a high-growth startup environment - Preferred: Fintech experience with payments or transaction-level data; Master's or PhD in data science, ML, statistics, or quantitative field; PySpark and Databricks