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AI Regulatory Filing Analyst

Layla Suzuki

Full-time · Job · Chicago

About the role

SEC filings are dense, repetitive, and full of legally precise language that hides meaningful information in plain sight. Our AI reads them so investment analysts don't have to — extracting key metrics, flagging material changes from prior filings, and generating structured summaries that highlight what actually matters. As a junior analyst, you'll work on the quality side: evaluating AI extraction accuracy against manually reviewed filings, building test datasets for edge cases (restatements, non-standard formats, foreign filers), and maintaining the evaluation pipeline that tracks extraction quality over time. You'll learn how financial documents work from the inside. By the end of your first year, you'll understand 10-K filings better than most junior analysts at investment banks — and you'll know how to build AI that reads them.

Responsibilities

  • Evaluate AI extraction accuracy against manually reviewed SEC filings
  • Build test datasets for edge cases in filing formats and structures
  • Maintain evaluation pipelines tracking extraction quality over time
  • Analyze error patterns and recommend improvements to the extraction engine
  • Document evaluation methodology and maintain filing format references

Requirements

  • Python proficiency with pandas for data analysis
  • SQL skills for querying filing databases
  • Strong reading comprehension and analytical skills
  • Interest in finance or financial document analysis
  • Attention to detail and systematic approach to evaluation

Benefits

  • Fully remote — US time zones
  • Health insurance
  • Mentorship from senior financial analysts
  • $1,500 learning budget

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Categories

NLP & Prompt Engineering data science & analytics

Skills

python openai api langchain sql pandas

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

Under $60k / year

AI Expertise

NLP & Prompt Engineering data science & analytics

Skills

python openai api langchain sql pandas

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