Lead Data Scientist, Computational Oncology

RiseMe; Boston (MA); Hybrid; USD 160,000 - 251,000; Full time

Job summary

Merck in Boston, MA (hybrid) is seeking an Associate Director of Data Science for Computational Oncology. You will lead analyses of large oncology datasets and oversee functional genomics screens to nominate targets and drug combinations, applying advanced statistics and ML to integrate multi-omics data.

You will collaborate across experimental, AI/ML, and data science teams to produce robust conclusions and translational insights for Discovery Oncology.

Qualifications

• PhD in quantitative STEM (e.g., computational biology, bioinformatics).
• MS with 8+ years of relevant experience; OR BS with 12+ years.
• Strong statistical foundation; experience with cancer genomics.

Responsibilities

• Analyze large-scale oncology datasets (bulk RNA-seq, WES/WGS, scRNA-seq) to understand disease biology.
• Analyze functional genomics screens (CRISPR, Perturb-seq) from QC to interpretation to establish targets.
• Nominate and prioritize drug combinations by weighing multi-omics evidence.
• Apply rigorous statistics and integrate multi-omics data with prior knowledge.
• Apply deep learning and foundation models to cell-type deconvolution and patient stratification.
• Use AI and retrieval over internal data to accelerate evidence synthesis.
• Translate preclinical findings to patient biology through cross-team collaboration.
• Ensure reproducible, well-documented research in Discovery Oncology.

Skills

Bioinformatics

Biostatistics

Cancer Genomics

CRISPR-Cas System

Data Modeling

Data Science

Machine Learning

Genomics

Omics

Oncology

Stakeholder Management

Education

PhD in quantitative STEM (e.g., computational biology, bioinformatics)

MS with 8+ years experience

BS with 12+ years experience

Tools

AWS

Nextflow

Databricks

Posit

Git

Linux

Job description

Merck in Boston, MA (hybrid) is seeking an Associate Director of Data Science for Computational Oncology. You will lead analyses of large oncology datasets and oversee functional genomics screens to nominate targets and drug combinations, applying advanced statistics and ML to integrate multi-omics data.

You will collaborate across experimental, AI/ML, and data science teams to produce robust conclusions and translational insights for Discovery Oncology.