Director, Oncology Data Science
Merck
June 24, 2026
Remote friendly (Boston, MA)
United States
IT
Director of Oncology Biomarker Discovery — Oncology Data Science
Responsibilities
- Investigate proprietary and public real-world molecular datasets and clinical trials using tissue and periphery assays to identify robust multimodal biomarkers of response/resistance across indications and lines of therapy, with line of sight to diagnostic development.
- Use advanced AI/ML to integrate multi-modal data (RNAseq, WES, ctDNA, digital pathology, proteomics, immune activation assays, liquid biopsies) to discover biomarkers, molecular patient groups, and mechanisms of therapeutic response reflected in longitudinal analytes.
- Present analyses and partner with stakeholders across Translational Oncology, Molecular Diagnostics, Clinical Development, Statistics, Therapeutic Area Biology, and Commercial Development.
Qualifications
- Education: M.S. (12+ years) or Ph.D. (8+ years) in Engineering, Applied Mathematics, Bioinformatics, Computational Biology, or related field; significant computational and statistical expertise; pharma/biotech/academic experience.
Required Experience/Skills
- Extensive experience applying computational methods in cancer biology.
- Expertise with scientific cloud-based computation; R/Python highly preferred.
- AI/ML experience (supervised/unsupervised ML, foundation models) and modern coding.
- Genomic datasets across cancer types/therapeutic modalities with demonstrated impact on drug development.
- Hands-on algorithms for large genetic/genomic/immunogenomic/clinical datasets (e.g., TCGA, GTEx, DepMap, CPTAC) and RWD genomic, imaging, and EHR.
- Experience leading computational scientists; strong communication and data-driven influence.
Preferred Experience/Skills
- Genomic trial analysis; companion diagnostic development (preferably NGS); statistical learning/data mining expertise; matrix collaboration; high-profile publishing.
Required Skills
AI, Cancer Genomics, Cancer Research, Cloud Computing, Computational Methods, Data Science, Genomic Data Analysis, Machine Learning (ML), Multimodal, Multimodal Analysis, Oncology
Application
- Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub). Deadline is stated on the posting.
Responsibilities
- Investigate proprietary and public real-world molecular datasets and clinical trials using tissue and periphery assays to identify robust multimodal biomarkers of response/resistance across indications and lines of therapy, with line of sight to diagnostic development.
- Use advanced AI/ML to integrate multi-modal data (RNAseq, WES, ctDNA, digital pathology, proteomics, immune activation assays, liquid biopsies) to discover biomarkers, molecular patient groups, and mechanisms of therapeutic response reflected in longitudinal analytes.
- Present analyses and partner with stakeholders across Translational Oncology, Molecular Diagnostics, Clinical Development, Statistics, Therapeutic Area Biology, and Commercial Development.
Qualifications
- Education: M.S. (12+ years) or Ph.D. (8+ years) in Engineering, Applied Mathematics, Bioinformatics, Computational Biology, or related field; significant computational and statistical expertise; pharma/biotech/academic experience.
Required Experience/Skills
- Extensive experience applying computational methods in cancer biology.
- Expertise with scientific cloud-based computation; R/Python highly preferred.
- AI/ML experience (supervised/unsupervised ML, foundation models) and modern coding.
- Genomic datasets across cancer types/therapeutic modalities with demonstrated impact on drug development.
- Hands-on algorithms for large genetic/genomic/immunogenomic/clinical datasets (e.g., TCGA, GTEx, DepMap, CPTAC) and RWD genomic, imaging, and EHR.
- Experience leading computational scientists; strong communication and data-driven influence.
Preferred Experience/Skills
- Genomic trial analysis; companion diagnostic development (preferably NGS); statistical learning/data mining expertise; matrix collaboration; high-profile publishing.
Required Skills
AI, Cancer Genomics, Cancer Research, Cloud Computing, Computational Methods, Data Science, Genomic Data Analysis, Machine Learning (ML), Multimodal, Multimodal Analysis, Oncology
Application
- Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub). Deadline is stated on the posting.