Senior Data Scientist – Surfaceome Biology Job at Amgen (Hyderabad)

Senior Data Scientist – Surfaceome Biology

Amgen

Location:
India , Hyderabad

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

We are seeking a highly qualified and motivated Senior Data Scientist with a strong background in computational biology to join the Bioinformatics Technologies team within Amgen’s Automation, Research Data Systems, Informatics, and AI (ARIA) organization. ARIA is a multidisciplinary group embedded within Amgen’s discovery engine, leveraging advancements in digital technologies for disease modeling and digital modality engineering to accelerate the pipeline from target inception through drug development. Within ARIA, Bioinformatics Technologies serves as an innovation hub for developing, deploying, and applying emerging digital technologies in computational biology to drive the next generation of therapeutic discovery.

Job Responsibility:

Develop novel AI/ML, computational, and data science methods – including agentic AI systems – for processing, integrating, and analyzing multi-modal datasets (e.g., transcriptomics, proteomics, imaging, and single-cell multi-omics) to identify and prioritize novel and target-tissue specific cell surface antigens
Build workflows to harmonize and integrate public and internal datasets for constructing comprehensive multi-modal surfaceome atlases, and model protein expression heterogeneity across cell types, states, and spatial contexts
Design computational tools and predictive models for protein localization, topology, and internalization behavior to prioritize candidate surface proteins or antigen–ligand pairs for the discovery of multispecific antibody modalities and therapeutic payload delivery
Apply generative modeling and representation learning to propose novel antigen candidates or antigen combinations with desirable therapeutic attributes, such as accessibility, specificity, and internalization potential
Collaborate with experimental and translational teams to design and guide validation experiments, ensuring computational predictions translate into actionable biological insights

Requirements:

Any degree and 8-13 years of directly related experience
Demonstrated expertise in computational and data science method development for short- and long-read transcriptomics, polysome sequencing, proteomics, multi-omics integration, or surfaceome characterization
Strong background in machine learning and AI, including deep learning and generative modeling
experience with pre-training, fine-tuning, and few-/zero-shot learning, ideally experience with in silico modeling of cellular surface protein biology
Proven track record of applying computational methods to drive biological insights, target validation, biomarker discovery, or therapeutic hypothesis generation
Proficiency in scientific programming languages and tool development using Python, R, or similar, with familiarity in relevant libraries and frameworks
Experience with large-scale data processing using cloud computing, workflow development, and software best practices (e.g., version control, continuous integration, test-driven development)
Familiarity with agentic AI, digital innovation approaches, and FAIR data principles for building robust and scalable analytical workflows
Familiarity with molecular and disease biology, with the ability to contextualize computational findings in therapeutic discovery
Excellent analytical and communication skills, with the ability to extract and clearly present insights from complex data to diverse audiences with rigor and accuracy
Strong interpersonal and collaborative skills with demonstrated ability to thrive in cross-functional teams and effectively present results to diverse audiences
Creative, open-minded, and passionate about research, with a proven record of innovative algorithm and model development demonstrated through impactful publications, patents, or widely adopted tools