Senior Data Scientist – Perturbation Biology & AI

Overview

Senior Data Scientist with a strong computational biology background to join the Bioinformatics Technologies team within Amgen's ARIA organization, developing and applying advanced computational and AI/ML methods to analyze perturbation screening data for target and therapeutic discovery.

What you'll do

• Develop and apply advanced methodologies at the intersection of functional genomics and AI/ML analytics to identify and validate novel therapeutic targets, elucidate mechanisms of action, and discover preclinical biomarkers.
• Provide computational and data science support for high-throughput single-cell perturbation and phenotypic screening experiments (e.g., Perturb-seq) to map gene–phenotype relationships, uncover disease drivers, and prioritize hits for validation.
• Drive digital innovation by identifying gaps in analytical workflows and developing robust, reproducible, and FAIR solutions that improve data interpretability, strengthen readout confidence, and accelerate therapeutic hypothesis generation.
• Build and apply machine learning, deep learning, and generative AI approaches to simulate cellular responses to single or combinatorial genetic and non-genetic perturbations, delivering fit-for-purpose predictions that reduce experimental burden.
• Collaborate closely with experimental biologists and translational teams to ensure computational predictions align with experimental design and biological context, enabling testable target and biomarker hypotheses.
• Contribute to the design of perturbation experiments so that computational and experimental approaches inform and strengthen each other.

What you'll need

• Any degree and 8-13 years of directly related experience

Nice to have

• Demonstrated expertise in method development for functional genomics and perturbation screens, ideally with experience in single-cell omics technologies.
• Strong background in machine learning and AI, including deep learning, generative modeling, and transformer-based architectures; experience with pre-training, fine-tuning, and few-/zero-shot learning, ideally with experience in in silico modeling of cellular responses to drug or genetic perturbations.
• 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.

Details

• Location: Hyderabad, India