Associate Director, Data Science
Merck
August 22, 2026
On-site
Boston, MA
IT
The Translational Genome Analytics group is recruiting an Associate Director (Associate Principal Scientist) to join its data science team.
Responsibilities:
- Perform reverse translation from clinical datasets to enable biomarker discovery, combination strategies, and novel target identification for molecularly defined patient populations.
- Analyze, summarize, and visualize findings from large multi-modal clinico-genomic datasets (bulk RNA-seq, WES/WGS, imaging, epigenetic profiling, single-cell RNA-seq, proteomics).
- Use deep learning/AI and multivariate predictive modeling to discover novel biomarkers predictive of clinical outcomes; apply statistical inference and/or deep learning to integrative analysis of multimodal, high-dimensional tumor profiling data.
- Collaborate with AIML teams developing foundation models trained on large cohorts of human data.
Qualifications:
- Master’s (8+ years) or Ph.D. (4+ years) in a quantitative field (e.g., Engineering, Applied Physics/Mathematics, Bioinformatics, Computational Biology) with substantial computational/statistical experience.
Required Experience/Skills:
- Statistical learning and data mining expertise for integrative analysis of multimodal, high-dimensional molecular profiling datasets in oncology/immuno-oncology.
- Hands-on experience with large genetic/genomic/immunogenomic/clinical datasets (e.g., IEDB, TCGA, GTEx, DepMap).
- Proficiency coding in R/Python and/or MATLAB with reproducible-analysis best practices.
- Strong communication/presentation skills; ability to guide decisions with data-driven hypotheses.
- Independent, flexible, collaborative mindset.
Preferred:
- Clinical-trials genomic analysis; cancer biology knowledge; cross-disciplinary collaboration in matrix environments; high-profile publications.
Skills: Cancer Biology, Computational Biology, Data Analysis, Data Mining, Data Science, Genomic Data Analysis, Immuno-Oncology, MATLAB, Multimodal Analysis, Python, R, Statistical Analysis, Statistical Learning.
Application:
- Apply via https://jobs.merck.com/us/en. Application deadline is stated on the posting.
Responsibilities:
- Perform reverse translation from clinical datasets to enable biomarker discovery, combination strategies, and novel target identification for molecularly defined patient populations.
- Analyze, summarize, and visualize findings from large multi-modal clinico-genomic datasets (bulk RNA-seq, WES/WGS, imaging, epigenetic profiling, single-cell RNA-seq, proteomics).
- Use deep learning/AI and multivariate predictive modeling to discover novel biomarkers predictive of clinical outcomes; apply statistical inference and/or deep learning to integrative analysis of multimodal, high-dimensional tumor profiling data.
- Collaborate with AIML teams developing foundation models trained on large cohorts of human data.
Qualifications:
- Master’s (8+ years) or Ph.D. (4+ years) in a quantitative field (e.g., Engineering, Applied Physics/Mathematics, Bioinformatics, Computational Biology) with substantial computational/statistical experience.
Required Experience/Skills:
- Statistical learning and data mining expertise for integrative analysis of multimodal, high-dimensional molecular profiling datasets in oncology/immuno-oncology.
- Hands-on experience with large genetic/genomic/immunogenomic/clinical datasets (e.g., IEDB, TCGA, GTEx, DepMap).
- Proficiency coding in R/Python and/or MATLAB with reproducible-analysis best practices.
- Strong communication/presentation skills; ability to guide decisions with data-driven hypotheses.
- Independent, flexible, collaborative mindset.
Preferred:
- Clinical-trials genomic analysis; cancer biology knowledge; cross-disciplinary collaboration in matrix environments; high-profile publications.
Skills: Cancer Biology, Computational Biology, Data Analysis, Data Mining, Data Science, Genomic Data Analysis, Immuno-Oncology, MATLAB, Multimodal Analysis, Python, R, Statistical Analysis, Statistical Learning.
Application:
- Apply via https://jobs.merck.com/us/en. Application deadline is stated on the posting.