Senior Data Scientist - Protein Data Pipelines
Amgen (company site, opens in a new tab)6+ yrsHyderabadOn-siteDirect career pageEst. 20–38 LPA
Posted on 9 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain scalable, quality-controlled data pipelines specifically for protein sequence, structure, and function to support predictive model training and reuse across research programs.
- Develop and own reusable frameworks for ML model deployment, inference, validation, and monitoring to integrate trained models into ongoing projects reliably.
- Facilitate cross-functional collaboration between ML developers, wet-lab scientists, and domain experts to align data, modeling, and experimental requirements and coordinate technical delivery across distributed teams.
Minimum Requirements
- Bachelor's degree in Computational Biology, Bioinformatics, Life Sciences, Computational Chemistry, Chemical Engineering, Materials Science, Data Science, or related quantitative field with relevant experience.
- Experience Requirement: Bachelor's degree with 6+ years relevant experience, or Master's degree with 4+ years relevant experience, or PhD.
- Strong experience building scalable data pipelines using Python and/or SQL; experience with pipeline automation tools like Databricks preferred.
- Hands-on experience managing end-to-end MLOps for machine learning models, including deployment and inference workflows.
Ideal Candidate Profile
- Experience bridging scientific domains (e.g., computational biology, chemistry, materials science) with data engineering and MLOps to support predictive modeling of protein data.
- Proven ability to build reusable, maintainable data and model deployment systems that scale across discovery pipelines and enable reproducibility and data quality control.
- Skilled in coordinating cross-disciplinary technical teams and translating complex scientific and engineering needs into reliable production-ready solutions.