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AI Supplier Lead Time Variability Analyst

Dylan Oliveira

Full-time · Job · Chicago

About the role

Our clients include manufacturers who plan procurement months in advance, and the single biggest source of plan disruption isn't supplier failure, it's lead times that are technically met but wildly inconsistent from order to order. You will build models quantifying lead time variability per supplier and product category, distinguishing genuinely unreliable suppliers from ones with predictable seasonal swings, and feed that into procurement planning buffers. You'll present findings directly to procurement leadership at client organizations, whose buffer stock decisions will be shaped by your models.

Responsibilities

  • Build models quantifying supplier lead time variability by category and season
  • Distinguish genuinely unreliable suppliers from those with predictable seasonal patterns
  • Feed variability estimates into client procurement buffer planning
  • Validate model output against actual delivery outcomes each quarter
  • Present findings directly to client procurement leadership

Requirements

  • 6+ years in applied data science, ideally supply chain or procurement analytics
  • Strong SQL and statistics background
  • Comfortable presenting quantitative findings to operations leadership
  • Experience with time-series or variability modeling

Benefits

  • Fully remote position
  • Health, dental, and vision insurance
  • Equity package
  • Annual company offsite

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Categories

data science & analytics AI Business, Marketing & Strategy

Skills

python sql statistics

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$100k – $130k / year

AI Expertise

data science & analytics AI Business, Marketing & Strategy

Skills

python sql statistics

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