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AI Synthetic Test Data Engineer

Lillian Nguyen

Full-time · Job · Chicago

About the role

Testing with production data is a liability lawsuit waiting to happen. Our synthetic data platform generates realistic test datasets that preserve the statistical properties of production data — distributions, correlations, edge cases — without containing a single real record. Banks, hospitals, and government agencies use our platform to test their systems safely. As a junior engineer, you'll help build and maintain the generators that produce synthetic data for specific domains: financial transactions, patient records, logistics shipments. Each domain has unique constraints — a synthetic credit card transaction needs realistic merchant categories, amounts, timestamps, and fraud patterns. A synthetic patient record needs consistent diagnoses, medications, and lab results. You'll learn the statistics behind synthetic data generation: distribution fitting, copula models, differential privacy budgets, and the evaluation metrics that prove synthetic data is both realistic and private. Your senior teammate built the core generation framework; you'll extend it to new domains and improve quality on existing ones.

Responsibilities

  • Build and maintain synthetic data generators for specific industry domains
  • Implement statistical quality checks to validate synthetic data realism
  • Extend the generation framework with new data types and constraints
  • Write tests that verify privacy guarantees of generated data
  • Document domain-specific generation rules and evaluation criteria
  • Support client onboarding with custom generator configurations

Requirements

  • 1+ year of Python development with basic statistics knowledge
  • Familiarity with pandas and data manipulation
  • Understanding of probability distributions and sampling methods
  • Interest in data privacy and synthetic data concepts
  • Ability to write clean, well-tested code

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • $1,500 learning budget
  • Mentorship from senior data scientists
  • Clear career progression framework

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Categories

MLOps & AI Infrastructure data science & analytics

Skills

python sql pandas docker aws

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Job Type

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Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

python sql pandas docker aws statistics

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