Data Scientist

Metabolon is seeking a skilled and experienced  Data Scientist to join our team. In this role, you will leverage your strong computational background and bioinformatics expertise to develop and maintain robust pipelines and computational methods, particularly in the domain of metabolomics and other omics. You will be responsible for managing machine learning (ML) pipelines end-to-end, including feature extraction, model training, and deployment. A solid understanding of LC-MS data processing, particularly in peak alignment and identification, is crucial. The ideal candidate will have experience in developing computational methods for metabolomics data and possess a basic knowledge of app frameworks such as Django, Flask, Streamlit, or Dash.

• Develop and maintain ML pipelines, including feature extraction, model training, and deployment.
• Apply your expertise in bioinformatics to design and develop computational methods for metabolomics data analysis.
• Work with cross-functional teams to integrate complex biological data into software applications.
• Utilize advanced machine learning methods such as regression, clustering, and classification to analyze and interpret omics data.
• Employ best practices in data processing, including peak alignment and identification for LC-MS data.
• Stay current with the latest developments in machine learning, data processing, and bioinformatics.
• Contribute to the development of user-friendly interfaces using app frameworks like Django.
• Regularly report and present your work to both technical and non-technical stakeholders.

• Strong computational background with the ability to write efficient code, ideally in python.
• Solid understanding of common steps in LC-MS data processing, particularly in peak alignment and identification.
• Strong knowledge of fundamental machine learning methods, including regression, clustering, and classification.
• Experience in maintaining ML pipelines from feature extraction to model deployment.
• Basic knowledge of metabolomics and other omics.
• Experience in developing computational methods for metabolomics data.
• PhD or Master’s degree in Bioinformatics, Computational Biology, Data Science, or a related field (preferred).
• Knowledge of advanced regression methods, such as Ridge, Lasso, and Gaussian Process regression, is a plus.
• Basic knowledge of app frameworks like Django, Flask, Streamlit, or Dash.
• Excellent communication, collaboration, and project management skills.
• Familiarity with cloud platforms (e.g., AWS) and containerization tools (e.g., Docker) is an advantage.
• Experience with coding source control (e.g., git) and code testing practices is a plus.