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Senior Scientist – Data Science
| Company | Merck |
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| Location | San Bruno, CA, USA |
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| Salary | $156500 – $246300 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior |
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Requirements
- A Master’s (with 5 years) or Ph.D. in Statistics, Biostatistics, Computer Science/Data Science or related disciplines
- Extensive experience in the computational analysis and biological interpretation of diverse large-scale protein profiling datasets generated from high-dimensional imaging analysis
- Skilled in integrating results from multiple omics data sources and biological knowledge bases to customize analytical approaches for discovery research
- Proficient in applying and implementing both fundamental and advanced statistical techniques for non-clinical and clinical studies
- Strong programming skills with applications in imaging (e.g., Python, MATLAB) and statistical analysis (e.g., R)
- Exhibits a strong capacity for learning, maintaining a proactive and motivated approach, and consistently focusing on detail and execution
- Exceptional oral and written communication skills
Responsibilities
- Implement innovative data analytical tools and statistical methodologies to transform complex biomarker data into insights that can be readily used in drug development
- Perform data mining and data wrangling on large-scale datasets derived from image analysis to understand target biology, mechanisms of action, and to help identify potential clinical biomarkers
- Integrate high-throughput assays, including genomics, transcriptomics, and proteomics imaging datasets
- Develop end-to-end data visualization tools and conduct spatial analyses to understand and interpret complex high-dimensional data
- Collaborate proactively across disciplines, engaging with pathologists, machine learning scientists, molecular biologists, protein scientists, bioinformaticians, and software engineers
Preferred Qualifications
- Knowledge and experience in computational analysis for image-based histological or tissue-based assay readouts
- Previous experience in the experimental design of biological assays, statistical hypothesis testing, and biological interpretation
- Experience in version control environments such as Git
- Proficient in working with high-performance Linux clusters and cloud computing environments
