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AI Data Simulation Engineer

Savannah Watanabe

Full-time · Job · Chicago

About the role

We serve ML teams who can't get enough real-world data to train on, and synthetic data generation is how we close that gap for dozens of clients across healthcare, finance, and retail. You'll help build simulation pipelines that generate statistically realistic tabular datasets using NumPy and scikit-learn, then validate that the synthetic data preserves the statistical properties clients actually need for training. Expect close pairing with our synthetic data engineers and data augmentation researchers, who will review your validation results before any dataset ships to a client.

Responsibilities

  • Build simulation pipelines generating synthetic tabular datasets
  • Validate statistical fidelity of generated data with pandas and numpy
  • Support senior engineers on client-specific data augmentation requests
  • Document known limitations of each synthetic dataset

Requirements

  • 1-2 years of experience with Python data tooling
  • Basic statistics and scikit-learn familiarity
  • Attention to detail when validating data quality
  • Willingness to learn synthetic data generation techniques on the job

Benefits

  • Fully remote position
  • Mentorship from senior data engineers
  • Health insurance
  • Learning stipend

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$80k – $100k / year

AI Expertise

data science & analytics MLOps & AI Infrastructure

Skills

python numpy scikit-learn pandas statistics

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