Senior Data Scientist - Protein Structure ML models
Amgen (company site, opens in a new tab)6+ yrsHyderabadOn-siteDirect career pageEst. 28–48 LPA
Posted on 9 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and validate machine learning models to predict protein function from structure, focusing on antibodies and antibody-like molecules.
- Design and maintain validation benchmarks for antibody binding models using internal and external datasets to support model selection and quality control.
- Partner with wet-lab scientists to guide experimental data generation and integrate protein structure prediction, generation, and inverse-folding tools into reproducible protein design workflows.
Minimum Requirements
- Bachelor’s degree with 6+ years relevant experience, OR Master’s degree with 4+ years relevant experience, OR PhD in relevant quantitative or life science field.
- Proficiency in Python and experience with modern deep learning frameworks such as PyTorch or JAX.
- Strong hands-on experience in protein structure modeling, especially related to antibodies.
- Experience applying deep learning methods to protein structural data, including graph neural networks or equivariant models.
Ideal Candidate Profile
- Has combined expertise in machine learning and protein structure modeling related to biologics discovery and antibody engineering.
- Experienced in developing and adapting ML models and designing validation strategies for real-world discovery impact.
- Comfortable collaborating across disciplines including computational biology, structural biology, protein engineering, and experimental teams to integrate ML workflows into biologics design pipelines.