Lead, Functional Genomics Data Science & AI

MSD Malaysia; South San Francisco (CA); On-site; USD 176,000 - 277,000; Full time

Job summary

Merck & Co., Inc. is seeking an Associate Director of Data Science to lead Functional Genomics analytics within the Translational Genome Analytics division in Cambridge, MA.

The role focuses on building scalable computational frameworks for CRISPR and multi-omics data, guiding target prioritization and drug combinations using AI/ML approaches. You will mentor scientists, shape discovery strategies, and collaborate across disciplines to accelerate early discovery, including integration with

Qualifications

• MS in computational biology, bioinformatics, biostatistics, biophysics, mathematics, statistics, genetics/genomics, CS or related STEM with 8+ years of experience.
• Experience analyzing large scale NGS and functional genomics datasets.
• Experience applying ML to single-cell RNA-seq data and integrating multi-omics data.
• Proficiency in R or Python and Git; familiarity with public data repositories.

Responsibilities

• Lead design and build scalable computational analytics frameworks for CRISPR screens and related data.
• Invent scalable methods for single-cell perturbation screening and lineage tracing.
• Integrate genomics, imaging, transcriptomics and proteomics data for target prioritization.
• Apply modern AI/ML and LLM-powered workflows to triage targets and synthesize evidence.
• Mentor a team of scientists and set technical direction for functional genomics analytics.

Skills

AWS

Bioinformatics

Computational Biology

NGS

Machine Learning

Python/R

Linux

Git

Education

MS in computational biology or related field

Tools

Git

Job description

Merck & Co., Inc. is seeking an Associate Director of Data Science to lead Functional Genomics analytics within the Translational Genome Analytics division in Cambridge, MA.

The role focuses on building scalable computational frameworks for CRISPR and multi-omics data, guiding target prioritization and drug combinations using AI/ML approaches. You will mentor scientists, shape discovery strategies, and collaborate across disciplines to accelerate early discovery, including integration with