Synthetic Data Engineer for Genomics Privacy

Mind Moves; Northern (KY); Hybrid; USD 138,000 - 179,000; Full time

Job summary

Mind Moves is seeking a contractor to design and build synthetic data generation pipelines for high-fidelity datasets used in testing AI systems handling sensitive data. You will prototype data solutions and apply privacy-preserving techniques in collaboration with NIH stakeholders.

The role offers remote work in the US, with EST time zone preference, and compensation ranging from $100 to $130 per hour. Contract duration is Sept–Dec, at 20–25 hours per week.

Qualifications

• Experience building synthetic data pipelines with statistical modeling or generative models (GANs/VAEs).
• Experience engineering large-scale genomic/clinical data formats and data transformations.
• Proficiency in Python and SQL with privacy/data science libraries.
• Data engineering/ETL and schema modeling experience.
• Familiarity with AI governance frameworks and federal compliance preferred.
• Eligible for US 1099 contracting; eligible for a federal public trust credential.

Responsibilities

• Design and build synthetic data generation pipelines that replicate data structures and statistics.
• Generate realistic synthetic test/dev datasets for prototyping and red-team testing.
• Apply privacy-preserving techniques, including differential privacy noise injection.
• Validate data fidelity and ensure parity with real data benchmarks.
• Document methods and assess residual privacy risks for releases.
• Collaborate with Red‑Team/Adversarial Security Lead and Biomedical Privacy Engineer.
• Produce methodology docs and data provenance records for DAC review.
• Coordinate with cross‑functional teams across federal agencies and partners.

Skills

Synthetic data pipelines

Statistical modeling

Generative models

Agent-based simulation

Python

SQL

PyTorch

Hail

Polars

Spark

Diffprivlib

Opacus

Tools

Hail

Polars

Spark

PyTorch

Job description

Mind Moves is seeking a contractor to design and build synthetic data generation pipelines for high-fidelity datasets used in testing AI systems handling sensitive data. You will prototype data solutions and apply privacy-preserving techniques in collaboration with NIH stakeholders.

The role offers remote work in the US, with EST time zone preference, and compensation ranging from $100 to $130 per hour. Contract duration is Sept–Dec, at 20–25 hours per week.