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Spade

Real-time transaction enrichment API for payments

Data Scientist – Mid & Senior Levels - AI/ML

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 3 years building and shipping models in Python in a fast-paced environment; senior candidates need at least 5 years.
  • Hands-on experience working with engineering and product teams, rather than exclusively in a research environment.
  • Strong machine learning, statistics, and data fundamentals, including PySpark, pandas, and SQL.
  • A product mindset, navigating ambiguity and optimizing for customer value as well as model accuracy.
  • Ability to take feedback and contribute to team success.
  • Use coding assistants and large language models in the workflow, with enthusiasm for further development.
  • Ability to work remotely within the United States or Canada; NYC-based candidates may alternatively work hybrid from the Flatiron headquarters two days per week.
  • For senior level: at least 5 years of experience and end-to-end ownership of machine learning/artificial intelligence products from idea to production.
  • For senior level: experience shipping machine learning/artificial intelligence-powered products, ideally customer-facing.
  • For senior level: track record of mentoring and raising team standards.

Responsibilities

  • Own the full lifecycle of machine learning/artificial intelligence products, from initial prototype to production systems serving customers.
  • Build automated systems, models, and pipelines that maintain data quality, accuracy, and coverage.
  • Set standards for building machine learning models that are accurate, scalable, robust, and production-ready.
  • For senior level, partner directly with leadership on roadmap and priorities.
  • For senior level, mentor other data scientists and raise team practices.

Desired Qualifications

  • Experience with Databricks, data pipelines, or Hex.
  • Experience with generative AI feature or product development.
  • Fintech experience, especially with transaction, merchant, or location data.
  • Experience at an early-stage, high-growth startup.

About the Company

Spade

Real-time transaction enrichment API for payments

Spade provides real-time transaction enrichment via an API that maps raw card transaction data to verified merchant identities, including granular category and geolocation details. The process starts when a client (such as a card issuer, neobank, or fraud platform) sends transaction data to Spade’s API; the system then matches the data to a real merchant identity, enriches it with additional attributes, and returns the enhanced transaction record to the client’s platform in under 50 milliseconds, enabling faster and more informed payment decisions during authorization. Spade serves fintechs and card ecosystems (examples include Ramp, Sardine, Unit, and Mercury) and differentiates itself through speed, real-time accuracy, and a security-conscious approach (SOC 2 certified and does not handle PII). The company's goal is to help clients improve authorization rates, strengthen fraud detection, and enable more capable card products by providing high-quality merchant data.

Company size
11-50
Company stage
Series B
Total funding
$62.4M
Headquarters
New York City, New York
Founded
2020

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