Hybrid ML Scientist: Synthetic Data & Data Harmonization

George Washington University; Rockville (MD); Hybrid; USD 38,000 - 62,000; Part time

Benefits offered by this job

Healthcare benefits

Benefits package

Job summary

The George Washington University’s Biostatistics Center in Rockville, MD seeks a Research Scientist specializing in machine learning, data harmonization, and privacy-preserving modeling. You will design pipelines to harmonize multi-site clinical and omics data, generate high-fidelity synthetic datasets, and ensure governance and compliance across large-scale studies.

Responsibilities include ETL/ELT development, privacy risk assessment, and collaboration with biostatisticians, privacy officers,

Qualifications

• Master's degree plus 5 years of related experience or a PhD with 2 years of related experience.
• Experience in research and/or higher education settings.
• Background in machine learning, data science, and data privacy desirable.

Responsibilities

• Lead synthetic data generation and privacy engineering activities for multi-site datasets.
• Design and validate generative models (GANs/VAEs/diffusion) for synthetic tabular and multi-omic data.
• Develop ETL/ELT pipelines to map multi-center data to common models (OMOP CDM, PCORnet).
• Collaborate with statisticians, privacy officers, and engineers to deliver secure data products.

Skills

ML

Data Harmonization

Privacy Engineering

Synthetic Data

Education

Master's degree + 5 years experience

PhD + 2 years experience

Tools

Bioconductor

PLINK

Nextflow

Snakemake

Docker

Kubernetes

Git

R

Python

SQL

Job description

The George Washington University’s Biostatistics Center in Rockville, MD seeks a Research Scientist specializing in machine learning, data harmonization, and privacy-preserving modeling. You will design pipelines to harmonize multi-site clinical and omics data, generate high-fidelity synthetic datasets, and ensure governance and compliance across large-scale studies.

Responsibilities include ETL/ELT development, privacy risk assessment, and collaboration with biostatisticians, privacy officers,