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AI ESG Data Extraction Pipeline Developer

Chloe Schneider

Full-time · Job · New_York

About the role

ESG reporting is a mess. Companies disclose environmental, social, and governance data in annual reports, sustainability filings, and investor presentations — each using different metrics, timeframes, and definitions. An investor trying to compare carbon emissions across 50 companies faces 50 different disclosure formats, 30 different emission calculation methodologies, and zero standardization. Our extraction pipeline reads these diverse disclosures and pulls structured ESG metrics into a standardized database. You'll build the document processors that identify ESG data tables, extract numeric values with their units and time periods, and normalize them into our unified schema. The challenge is handling the long tail of reporting formats — every company invents its own way of presenting essentially the same information. The ESG data team is three engineers. You'll start with the table extraction module, learning how companies present ESG metrics. Your senior teammate handles the normalization logic that maps extracted values to standardized metrics. By month three, you'll process new company reports independently.

Responsibilities

  • Build document processors extracting ESG metrics from corporate disclosures
  • Identify and parse ESG data tables from diverse report formats
  • Extract numeric values with units, time periods, and methodology notes
  • Handle the long tail of non-standard reporting formats
  • Write extraction tests against annotated reference documents
  • Document extraction patterns for different disclosure frameworks

Requirements

  • 1+ year of Python development with data extraction experience
  • Basic understanding of document processing or NLP concepts
  • Familiarity with SQL databases and REST APIs
  • Interest in sustainability, ESG, or financial data
  • Systematic approach to handling messy real-world documents

Benefits

  • Fully remote with flexible hours
  • Health and dental insurance
  • $1,500 learning stipend
  • Mentorship from senior data engineers
  • Work that supports sustainable investing decisions

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Categories

data science & analytics Automation & AI Workflows

Skills

python sql langchain fastapi docker

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

Under $60k / year

AI Expertise

data science & analytics Automation & AI Workflows

Skills

python sql langchain fastapi docker pandas

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