Remote Bioinformatics Scientist - Biomarker Discovery

Mercy BioAnalytics; Waltham, Northern (MA, KY); Hybrid; USD 120,000 - 128,000; Full time

Job summary

Mercy BioAnalytics, Inc. is a biotechnology company focused on early cancer detection through biomarker discovery and data-driven approaches.

We are seeking a passionate Scientist to advance our Bioinformatics team, integrating public datasets with internal screening data to prioritize biomarkers and build scalable data infrastructure. The role emphasizes collaboration, cloud-based workflows, and AI-assisted pipelines to accelerate discovery for our life-saving programs.

Qualifications

• BSc/MS in bioinformatics, computational biology, or genomics with 5 years of industry experience, or a PhD.
• Working knowledge of cancer biology and biomarker development, including tumor heterogeneity.
• Expert-level Python and/or R, strong SQL, and Git.
• Cloud experience (AWS) and familiarity with workflow orchestration.
• Experience with single-cell RNA-seq analysis and co-expression questions preferred.
• Experience building analytical apps with Shiny or Streamlit.

Responsibilities

• Biomarker Discovery and Prioritization integrating public and internal datasets.
• Develop a biomarker prioritization framework considering tumor specificity and accessibility.
• Extend prioritization to marker combinations and single-cell analyses.
• Analyze internal data including QC, normalization, and hit calling.
• Collaborate with lab team on screening design and candidate evaluation.
• Design and build data warehouse and self-service dashboards.

Skills

Python

R

SQL

Git

Shiny/Streamlit

AI tooling

Cloud computing

Education

PhD

BSc/MS in bioinformatics / related field

Tools

AWS

Airflow

Docker

Kubernetes

Job description

Mercy BioAnalytics, Inc. is a biotechnology company focused on early cancer detection through biomarker discovery and data-driven approaches.

We are seeking a passionate Scientist to advance our Bioinformatics team, integrating public datasets with internal screening data to prioritize biomarkers and build scalable data infrastructure. The role emphasizes collaboration, cloud-based workflows, and AI-assisted pipelines to accelerate discovery for our life-saving programs.