Clinical ML Data Scientist: Flow Cytometry & MRD

St. Jude Children's Research Hospital; Lauderdale Courts (TN); On-site; USD 126,000 - 238,000; Full time

Job summary

St. Jude Children's Research Hospital is seeking a Data Scientist to lead ML solutions for high-dimensional clinical flow cytometry data and MRD detection, collaborating with faculty and laboratory leadership to translate questions into computational workflows.

The role involves building scalable, validated analytics, automating pipelines, and delivering data products for clinical implementation, regulatory review, and publication.

Qualifications

• Bachelor's degree with 10+ years of post-degree experience, or Master's with 8+ years, or PhD with 5+ years.
• Substantial experience in at least one programming language and at least one statistical package, with R preferred.

Responsibilities

• Lead data analysis and deliver high-quality results by formulating advanced and innovative machine learning approaches to address clinical flow cytometry questions.
• Design, develop, validate, and maintain ML pipelines for supervised and unsupervised analysis of flow cytometry data.
• Deliver data products, analytical reports, visualizations, and technical documentation for clinical implementation and regulatory review.
• Document analytical methods, model performance, validation results, and quality assurance procedures.
• Establish reproducible workflows for ML applications in clinical flow cytometry and laboratory quality monitoring.
• Develop methods for longitudinal monitoring of assay performance and quality control.

Skills

Python

R

Machine Learning

Collaboration

Communication

Data Analysis

Education

PhD in a relevant field

MS in a relevant field

Bachelor's degree with extensive experience

Tools

FlowJo

Cytobank

Spectre

FlowCore

UMAP / t-SNE

Docker

Git

Job description

St. Jude Children's Research Hospital is seeking a Data Scientist to lead ML solutions for high-dimensional clinical flow cytometry data and MRD detection, collaborating with faculty and laboratory leadership to translate questions into computational workflows.

The role involves building scalable, validated analytics, automating pipelines, and delivering data products for clinical implementation, regulatory review, and publication.