Spade
Spade is the only transaction data enrichment solution backed by real data. We leverage our vast first-party data network to bring instant clarity and context to every purchase and payment—with precisely matched merchant, category, and geolocation details that empower you to build the next generation of financial technology.
2 - 10 employees
Senior Data Scientist
Job not on LinkedIn
November 10
Spade
Spade is the only transaction data enrichment solution backed by real data. We leverage our vast first-party data network to bring instant clarity and context to every purchase and payment—with precisely matched merchant, category, and geolocation details that empower you to build the next generation of financial technology.
2 - 10 employees
📋 Description
• Own ML/AI products end-to-end—from problem framing and prototyping to deployment, monitoring, and iteration • Develop and productionize ML/AI models for entity resolution, data enrichment, and quality improvements • Design and maintain end-to-end data workflows, pipelines, and testing frameworks for production systems • Collaborate with engineering, analytics, and product teams to translate ambiguous problems into shipped features • Use customer insights and internal metrics to identify new opportunities within Spade’s transaction data • Partner with leadership to define data science strategy, roadmaps, and best practices
🎯 Requirements
• 5+ years of industry experience in data science or machine learning • Bachelor’s degree in a relevant field • Deep expertise in machine learning, statistical modeling, deep learning, and entity resolution • Fluency in Python (including ML/statistical libraries) and SQL • Experience in high-growth startup environment • Nice to have: Experience in fintech, particularly with payments or transaction-level data • Nice to have: A Master’s or Ph.D. in data science, machine learning, statistics, or another quantitative field • Nice to have: Experience with PySpark and Databricks
🏖️ Benefits
• Equity grant will also be provided • We aim to pay fairly and competitively
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