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AI Water Stress Risk Mapping Engineer

Chloe Schneider

Full-time · Job · London

About the role

Our mission is to give companies an honest picture of the environmental risk hiding in their supply chains, and water scarcity is one of the least understood parts of that picture. Fresh water shortages are already disrupting manufacturing in multiple regions, and most companies find out only after a plant goes offline. You'll build the modeling layer that combines satellite hydrology data, regional consumption trends, and climate projections into facility-level water stress scores our clients use in supply chain risk reports. This is a senior, largely self-directed role: you'll define the modeling approach as much as implement it. You'll collaborate with our climate science advisors to make sure the statistical methodology holds up to external scrutiny, since these scores end up in client-facing sustainability disclosures.

Responsibilities

  • Build facility-level water stress risk models from satellite and climate data
  • Own the Spark-based pipeline that processes large hydrology datasets on GCP
  • Validate modeling methodology with external climate science advisors
  • Translate model output into client-facing risk scores and narratives

Requirements

  • 5+ years in environmental data science or geospatial modeling
  • Strong statistics background, comfortable in both Python and R
  • Experience with distributed data processing (Spark) at scale
  • Familiarity with GCP-based data infrastructure

Benefits

  • Fully remote across European hours
  • Health and dental coverage
  • Equity
  • Paid volunteer days for environmental causes

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python gcp spark statistics r

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

data science & analytics AI & Machine Learning Engineers

Skills

python gcp spark statistics r

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