Senior Data Scientist, Predictive Immune Biomarkers

Merck; Cambridge (MA); On-site; USD 145,000 - 228,000; Full time

Job summary

Merck is seeking a Senior Scientist, Predictive Immune Biomarkers (R3) to lead the development of foundation models and multi-omics analyses for patient stratification. You will work on integrating RNA-seq, spatial transcriptomics, and proteomics to identify predictive immune biomarkers in a fast-paced environment.

The role requires a PhD in a STEM field, strong programming in R/Python/Bash, and experience with HPC/AWS. Excellent communication and collaboration skills are essential.

Qualifications

• PhD in a STEM field (listed) with strong research track record in multi-omics.
• Proven experience building, fine-tuning, and benchmarking foundation models for biomarker tasks.
• Strong programming in R, Python, and Bash; HPC and AWS experience.
• Experience with QC/analysis of RNA-seq, spatial transcriptomics, and proteomics.
• Excellent written and verbal communication; ability to document methods clearly.

Responsibilities

• Build, evaluate and benchmark foundation models for predictive immune biomarkers.
• Perform QC/analysis of bulk and single-cell RNA-seq, spatial transcriptomics and proteomics data.
• Document analysis workflows and results; collaborate across teams.

Skills

Multi-omics analysis

Foundation models

R

Python

Bash

HPC

AWS

Biomarker discovery

Genomics

Data science

Education

PhD in STEM field

Tools

Limma

Seurat

scanpy

CosMx

10x Visium

OLINK

Mass spectrometry

Job description

Merck is seeking a Senior Scientist, Predictive Immune Biomarkers (R3) to lead the development of foundation models and multi-omics analyses for patient stratification. You will work on integrating RNA-seq, spatial transcriptomics, and proteomics to identify predictive immune biomarkers in a fast-paced environment.

The role requires a PhD in a STEM field, strong programming in R/Python/Bash, and experience with HPC/AWS. Excellent communication and collaboration skills are essential.