Amgen
Senior Data Scientist
India - Hyderabad
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hirly's read of this role
- Role family
- Data & ML
- Seniority
- Senior
- Country
- IN
- Work mode
- On-site / unstated
- First seen by hirly
- 28 Sept 2026
Derived automatically from the posting. Upload your resume above to see how the role scores against it.
the posting
Career Category
Clinical
Job Description
What you will do
Let's do this. Let's change the world. We are seeking a Senior Data Scientist with strong expertise in machine learning and predictive modeling to join the AI & Data for Engineered Biologics team within Amgen's Large Molecule Discovery (LMD) organization. In this vital role you will enable data-driven design and optimization of biologics by developing models that predict key developability and therapeutic properties. You will work with sequence, structure, and experimental datasets to generate actionable insights and guide discovery decisions.
The successful candidate will work in a highly collaborative, multidisciplinary environment, partnering with different experimental teams to build predictive models, train and evaluate protein foundation models, and design active-learning strategies that improve data generation and candidate optimization.
Key Responsibilities
Develop and apply predictive machine learning models for biologics properties, including developability and clinical immunogenicity-related endpoints
Train, fine-tune, and evaluate foundation models for sequence/structure-to-property prediction and biologics design
Integrate multimodal data, including protein sequence, structure, imaging, assay, and experimental metadata, to improve predictive performance and model robustness
Design active learning, uncertainty-aware, or Bayesian optimization strategies to prioritize experiments and guide data generation across modalities
Build reproducible modeling workflows and evaluation frameworks that support rigorous model comparison, validation, and deployment-readiness
Collaborate cross-functionally with scientists and software engineers to translate machine learning innovation into actionable insights for biologics discovery and optimization
Communicate scientific findings and modeling strategies through presentations, technical documentation, and cross-functional forums
What we expect of you
We are all different, yet we all use our unique contributions to serve patients. The collaborative professional we seek is a Senior Data Scientist with these qualifications.
Basic Qualifications
Doctorate degree with 4+yrs in Data Science, Computer Science, Computational Biology, Bioinformatics, Computational Chemistry, or a related field
Or
Master's degree and 8+ years of directly related experience
Preferred Qualifications
Experience developing machine learning models for biological, protein engineering, drug discovery or immunology applications
Strong proficiency in Python and experience with modern deep learning frameworks such as PyTorch
Experience with Python scientific computing tools, such as numpy, scipy, pandas, etc.
Experience with foundation models, representation learning, sequence-to-property modeling, and multimodal learning
Experience integrating sequence, structural, assay, imaging, and metadata sources into reliable, model-ready datasets
Proven ability to apply active learning, Bayesian optimization, uncertainty quantification and model interpretation to scientific problems
Experience working with large-scale datasets and in high-performance computing environments, including cloud-based platforms (e.g., AWS)
Familiarity with reproducible machine learning and software engineering practices, including version control (git), testing, containerization (Docker), workflow orchestration, data versioning, or experiment tracking.
Strong scientific communication skills, with publications in leading ML, computational biology, or protein science venues such as NeurIPS, ICML, ICLR, ISMB, Nature Biotechnology , Nature Methods , Cell Systems , MABS, PNAS or comparable conferences and journals; candidates should highlight representative publications on their resume.
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