Remote Bioinformatics Scientist — Liquid Biopsy & ML

Tempus AI; Chicago (IL); Hybrid; USD 100,000 - 140,000; Full time

Benefits offered by this job

Incentive compensation

Restricted stock units

Medical benefits

Job summary

Tempus AI seeks a Bioinformatics Scientist to advance liquid biopsy assays, develop ML models for oncology biomarkers, and validate analytical performance for regulatory submissions. The role bridges wet-lab science, clinical interpretation, and software engineering to deliver real-time genomic insights.

The candidate should lead with strong data science, cloud, and coding skills, contribute to cross-functional teams, and help scale production pipelines in a fast-paced biomedicine environment.

Qualifications

• PhD or Masters with 3+ years of industry experience in Bioinformatics, Computational Biology, Cancer Biology, Genetics, Immunology, Molecular Biology, or Computer Science
• Proficient with processing, aligning, and analyzing multimodal NGS data (epigenetics, DNA, RNA)
• Experience with Python and/or R and associated data science libraries

Responsibilities

• Develop assays, algorithms, ML models to analyze NGS and multimodal data for oncology biomarkers.
• Model tumor fraction estimation for longitudinal treatment response monitoring (TRM).
• Improve molecular barcoding filtering to distinguish true biomarkers from artifacts.
• Design classifiers to differentiate CHIP from tumor-derived variants and support regulatory submissions.
• Collaborate with wet-lab, medical directors, biostatisticians, software engineers and product managers.

Skills

Python

R

Machine learning

Statistics

Interdisciplinary teamwork

Education

PhD in relevant field

Master's with 3+ years experience

Tools

Docker

Nextflow

Snakemake

AWS

GCP

Job description

Tempus AI seeks a Bioinformatics Scientist to advance liquid biopsy assays, develop ML models for oncology biomarkers, and validate analytical performance for regulatory submissions. The role bridges wet-lab science, clinical interpretation, and software engineering to deliver real-time genomic insights.

The candidate should lead with strong data science, cloud, and coding skills, contribute to cross-functional teams, and help scale production pipelines in a fast-paced biomedicine environment.