Key Responsibilities :

• Design and implement robust computational and statistical methods to analyze large scale proteomics and metabolomics datasets.
• Develop automated data processing pipelines in collaboration with our cloud infrastructure team.
• Establish tools for the analysis, visualization, and reporting data in collaboration with scientists and other stakeholders.
• Collaborate closely with our chemoproteomics, synthetic biology, and metabolomics teams to identify and build enabling solutions.
• Integrate in-house datasets with public resources (GNPS, BioPlex, DepMap, etc.) to better understand disease biology and drive drug discovery programs.

Qualifications :

• Ph.D. with 1+ years or M.S. with 3+ years of relevant data science and software development experience
• High level of proficiency in programming languages such as Python and/or R.
• Experience working with biological and mass spectrometry data types including chemoproteomics, proteomics, metabolomics, and natural product structures
• Experience applying statistical and machine learning methods
• Extremely collaborative, innovative, and driven to add value to diverse projects