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AI Payment Method Preference Predictor

Cole Mueller

Full-time · Job · New_York

About the role

We serve over 500 merchants whose checkout conversion improves measurably every time the right payment method is offered first. Right now, that ordering is mostly static per region rather than personalized per shopper. You will build a model predicting which payment method a given shopper is most likely to complete checkout with, based on device, region, cart value, and historical behavior, feeding directly into checkout ordering logic. You'll own this model end to end and present quarterly conversion lift results directly to merchant success and product leadership.

Responsibilities

  • Build a model predicting shopper-level payment method preference at checkout
  • Own feature design incorporating device, region, and cart-value signals
  • Run controlled experiments measuring conversion lift from personalized ordering
  • Maintain Spark-based pipelines processing checkout event data at scale
  • Present quarterly conversion results to merchant success and product leadership

Requirements

  • 6+ years in applied data science, ideally payments or e-commerce
  • Strong SQL, statistics, and Spark experience
  • Track record running and interpreting controlled online experiments
  • Comfortable presenting business-facing results to leadership

Benefits

  • Fully remote position
  • Performance bonus tied to conversion impact
  • Health, dental, and vision insurance
  • Annual company offsite

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Categories

data science & analytics AI Business, Marketing & Strategy

Skills

python sql statistics spark

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

data science & analytics AI Business, Marketing & Strategy

Skills

python sql statistics spark

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