Bioinformatics Scientist

Job Summary:
**Responsibilities**:

- Work closely with clients to understand their metabolomics analysis needs and requirements, including familiarity with LC-MS/MS, MALDI workflows and data collection methods.
- Utilize expertise in mass spectrometry imaging (MSI) data analysis to provide insightful solutions and recommendations.
- Collaborate with team members to explore and implement new metabolomics R and python packages and ensure successful project execution within defined timelines.
- Understanding of spatially informed clustering algorithms and image registration techniques for MSI datasets.
- Collaborate with cross-functional teams, including biologists, chemists, and data scientists, to integrate metabolomics data with other omics data (genomics, proteomics) for comprehensive biological insights.
- Stay abreast of advancements in metabolomics technologies and methodologies, and implement cutting-edge techniques to enhance research capabilities.
- Generate comprehensive reports documenting analysis outcomes, findings, and recommendations.
- Collaborate with team members to ensure successful project execution within defined timelines.

**Requirements**:

- Ph.D. degree in a relevant field such as bioinformatics, computational biology, or chemistry plus 3 years of industrial/academic experience.
- Proven experience in metabolomics analysis and working with mass spectrometry imaging data, including LC-MS/MS workflow and data collection methods.
- Proficiency in programming languages such as Python and R, with the ability to learn new scientific packages.
- Strong understanding of metabolomics software tools, including Cardinal 3, ScanPy, and MSI-Segmentation.
- Experience with cloud computing platforms, particularly AWS, for data analysis and workflow development.
- Excellent analytical and problem-solving skills.

Polly delivers ML-ready biomedical molecular data for accelerated drug discovery. Hosting a rich repository of more than 230,000 multi-omic datasets, Polly curates data semi-automatically, with over 50,000 datasets added each month.

Polly offers 10x faster identification of therapeutic assets with high odds of success in the clinic. It has enabled the detection of multiple validated drug targets across immunology, oncology, and metabolic disorders. Polly supports discovery programs at Pfizer, Agios Pharmaceuticals, Genentech, and Yale and has 35+ research partners from premier biopharma companies and research labs.