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AI Test Data Generator

Lillian Nguyen

Full-time · Job · Chicago

About the role

QA teams need realistic test data, but production data is full of PII they can't use. Synthetic data generators produce data that looks realistic but misses the edge cases and correlations that cause real bugs. Our AI test data platform bridges this gap — generating data that preserves statistical properties and edge case distributions from production data, without exposing any real records. As a junior test data generator, you'll work on the data profiling and generation pipeline: analyzing production data schemas and distributions, configuring generation rules that preserve important correlations, validating that synthetic data triggers the same application behaviors as real data, and building the API that QA teams use to request custom test datasets. You'll learn an unusual niche — the intersection of data privacy, statistical analysis, and software testing. Companies that solve test data well ship software faster and more confidently.

Responsibilities

  • Profile production data schemas and statistical distributions
  • Configure synthetic data generation rules preserving edge cases and correlations
  • Validate that synthetic datasets trigger realistic application behaviors
  • Build and maintain the test data request API for QA teams
  • Document generation recipes for different data domains

Requirements

  • Python proficiency with pandas for data analysis
  • SQL skills for production schema analysis
  • Understanding of basic statistics and data distributions
  • Interest in software testing and data quality
  • Attention to detail for edge case identification

Benefits

  • Fully remote — US Central time zone
  • Health insurance
  • Mentorship from senior data engineers
  • $1,500 learning budget

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

Automation & AI Workflows

Skills

python openai api sql pandas fastapi

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