Associate Director, Functional Genomics, Data Science

Merck Merck · Pharma · MA

Associate Director for Functional Genomics Data Science at Merck, focusing on leading computational analytics for CRISPR screening programs. The role involves developing frameworks for data analysis, integrating omics and imaging data, and applying AI/ML, including LLM agentic workflows, to accelerate drug discovery. It requires managing scientists and ensuring reproducible research.

What you'd actually do

  1. Lead the design, development, and maintenance of scalable computational analytics frameworks for pooled, arrayed, single cell, and optical CRISPR screens, including QC pipelines, library design, and longitudinal readout analysis.
  2. Oversee and actively contribute to image analysis pipelines for high content and optical CRISPR screens, extracting biologically meaningful morphological features to support target prioritization.
  3. Integrate functional genomics and imaging derived results with high throughput transcriptomics and proteomics datasets to build multi evidence target prioritization packages for multiple stages of drug discovery.
  4. Leverage cutting edge AI and ML approaches, including LLM powered agentic workflows and network based methods, to accelerate target triage and automate biological evidence synthesis.
  5. Manage and mentor PhD level scientists, set the technical direction for the analytics sub team, and drive standards for reproducible research and FAIR data infrastructure.

Skills

Required

  • Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Statistics, Computer Science, Mathematics, Genetics/Genomics, or a related STEM field.
  • 4+ years of industry or applied academic experience.
  • computational analysis, algorithm development, and biological interpretation of large scale NGS and functional genomics datasets.
  • applying machine learning to analyze single cell RNA sequencing data
  • experimental design of biological assays, statistical hypothesis testing, and integrating results from multiple omics data sources.
  • R or Python
  • Git
  • AWS cloud computing infrastructure
  • Linux environments

Nice to have

  • post doctoral or relevant industry experience
  • leading an analytics team and mentoring scientists
  • functional genomics data, including CRISPR screen hit calling frameworks and library design interpretation.
  • optical pooled CRISPR screening image analysis pipelines and integrating morphological readouts with genomic datasets.
  • deep learning approaches to image based phenotypic profiling and cell classification for target identification.
  • general disease biology and immunology, with knowledge of the latest functional genomics research.
  • network based analysis frameworks or transfer learning techniques to infer gene regulatory patterns from NGS datasets.
  • building or deploying LLM powered systems or AI tools for biological data interrogation.
  • interactive data visualization tools, for example R Shiny, for multiomics readouts.

What the JD emphasized

  • lead the functional genomics analytics function
  • own the computational infrastructure, hit calling frameworks, and analytical tooling
  • technical and scientific leader
  • lead the design, development, and maintenance of scalable computational analytics frameworks
  • Oversee and actively contribute to image analysis pipelines
  • Manage and mentor PhD level scientists
  • set the technical direction
  • drive standards for reproducible research
  • proven track record of applying machine learning
  • hands on experience building or deploying LLM powered systems

Other signals

  • lead the design, development, and maintenance of scalable computational analytics frameworks
  • leverage cutting edge AI and ML approaches, including LLM powered agentic workflows
  • integrate functional genomics and imaging derived results with high throughput transcriptomics and proteomics datasets