Scientist, Biomarker Analysis

Amgen Technology; Hyderabad; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

Amgen Hyderabad is seeking a Biomarker Analysis Scientist to drive translational analytics across Oncology, Inflammation, Rare Disease and other programs. You will design and execute high-dimensional analyses, integrating multi-omics, imaging and clinical data to support drug development decisions.

The role operates within the Computational Biology and Translational Analytics function in Precision Medicine, requiring independence, deep technical skills, and strong communication with global

Qualifications

• PhD with 7+ years of relevant scientific experience OR MSc with 9+ years OR Bachelors with 11+ years of relevant scientific experience
• Experience analyzing complex, large-scale biological and clinical datasets including multi-modal and longitudinal data
• Strong background in statistical modeling, ML is a plus and translational/clinical context experience

Responsibilities

• Design, execute and interpret biomarker and translational analyses to support clinical development programs
• Develop analytical workflows for multi-omics, imaging, and clinical data
• Translate biological questions into quantitative analysis plans and models
• Integrate internal trial data with external datasets to contextualize findings
• Contribute to portfolio-level analyses and cross-asset learnings
• Collaborate with biologists, clinicians, assay scientists, and data engineers to ensure rigor and data quality
• Communicate analytical methods and conclusions to diverse audiences
• Collaborate across time zones with US/EU teams and leverage AI to enhance insights

Skills

R

Python

Statistics

Machine learning

Education

Doctorate degree in a quantitative field

Master's degree in a quantitative field

Bachelor's degree in a quantitative field

Tools

Git

tidyverse/R tidyverse

Job description

Location: India - Hyderabad (AIN)
Work Location Type: On-site
Organization: Global Development - Precision Medicine
People Leadership: No

Scope: Develop and deliver superior clinical biomarker analytics to Amgen clinical teams across the portfolio.

Join Amgens Mission of Serving Patients

At Amgen, our mission to serve patients living with serious illnesses drives everything we do. As Amgen expands its technology and innovation presence in Hyderabad, this role will be pivotal in delivering high-quality translational analytics to accelerates drug development through rigorous science, data, and responsible AI.

Role Summary

The Biomarker Analysis Scientist will play a critical role in advancing translational and reverse-translational insights from clinical trial data across Amgens global portfolio, including Oncology, Inflammation, Rare Disease, Cardiovascular Metabolic, and Obesity Related Diseases. This role is embedded within the Computational Biology and Translational Analytics function in Precision Medicine and is expected to operate with a high degree of scientific independence, technical depth, and cross-functional influence.

The successful candidate will be experienced with analytics within the drug development lifecycle and will design and execute rigorous biomarker and translational analyses using complex, high-dimensional clinical datasets, integrating multi-omics, imaging, and clinical metadata to support decision-making across early and late-stage development programs. This position requires strong biological intuition, advanced quantitative expertise, and the ability to communicate clearly and effectively with global, matrixed stakeholders.

This role is based at Amgens India site in Hyderabad and operates as part of a globally integrated Precision Medicine organization.

Key Responsibilities

• Design, execute, and interpret biomarker and translational analyses to support clinical development programs, including target engagement stratification, pharmacodynamic modeling, patient stratification, mechanism of action validation, indication selection, and benefitrisk assessments.

• Develop and apply robust analytical workflows for high-content, multi-modal clinical data, including bulk and single-cell genomics, transcriptomics, proteomics, metabolomics, epigenomics, spatial omics, imaging, and emerging assay modalities.

• Translate complex biological and clinical questions into quantitative analysis plans, statistical models, and computational frameworks that generate actionable insights.

• Integrate internal clinical trial data with external datasets (e.g., public omics resources, real-world data, literature-derived knowledge) to contextualize findings and inform program strategy.

• Contribute to portfolio-level analyses and cross-asset learnings through principled data mining, visualization, and knowledge discovery approaches.

• Partner closely with biologists, clinicians, assay scientists, and data engineering teams to ensure analytical rigor, data quality, and scientific relevance.

• Clearly communicate analytical approaches, assumptions, limitations, and conclusions to diverse audiences through written reports, presentations, and cross-functional forums.

• Operate effectively in a global, matrixed environment, including regular collaboration across time zones with US- and EU-based teams.

• Strategically leverage AI to enhance speed, accuracy and insightfulness of results, maximally integrating relevant findings in the public domain.

Basic Qualifications

• Doctorate degree with 7+ years of relevant scientific experience
  OR

• Masters degree with 9+ years of relevant scientific experience
  OR

• Bachelors degree with 11+ years of relevant scientific experience

Preferred Qualifications

Candidates are expected to demonstrate most of the following:

Scientific Technical Expertise

• PhD (or equivalent) in Bioinformatics, Computational Biology, Statistics, Applied Mathematics, Computer Science, Data Science, or a closely related quantitative discipline from a well-regarded institution

• Demonstrated experience analyzing complex, large-scale biological and clinical datasets, including multi-modal and longitudinal data

• Strong grounding in statistical modeling and methods (e.g., regression, mixed-effects models, multivariate methods, correlative and causal analysis, prognostic and predictive biomarker analysis farmeworks) and experience applying these methods in a translational or clinical context.Working knowledge of machine learning and AI methodologies, with practical experience applying them to biological or clinical data; experience in clinical trial settings is strongly preferred.

• Familiarity with clinical biomarker platforms and data types, such as NGS, flow cytometry, IHC, immunoassays, imaging, and transcriptional profiling.

• Proficiency in R and Python and version control (e.g. gitlab), with evidence of writing clear, reproducible, and maintainable analytical code; familiarity with modern data science ecosystems (e.g., tidyverse in R and equivalent libraries in python) and best practices in reproducible research.

Translational Impact Industry Experience

• Proven ability to connect molecular-level findings to clinical hypotheses and development decisions.

• Experience supporting drug development programs in a biotech or pharmaceutical setting (typically 3+ years).

• Working knowledge of assay development, validation, and qualification considerations for clinical trial support.

• Evidence of independent scientific contribution through peer-reviewed publications in reputable journals.

Collaboration, Communication Global Mindset

• Excellent written and spoken English communication skills, with the ability to explain complex analyses clearly to non-computational stakeholders.

• Demonstrated experience working effectively with global teams and stakeholders across geographies and time zones.

• Willingness and ability to operate flexibly across time zones to support global programs.

• Strong interpersonal skills characterized by intellectual humility, adaptability, curiosity, and a proactive approach to collaboration.

• Ability to think critically and creatively, ask clarifying questions, challenge assumptions constructively, and pivot analytical approaches as program needs evolve.

What Differentiates Top Candidates

• Clear evidence of end-to-end ownership of translational or biomarker analyses in clinical programs.

• Strong applied statistical background.

• Demonstrated impact on development decisions rather than purely methodological contributions.

• A track record of thriving in complex, ambiguous environments and driving alignment across scientific and technical teams.

• Experience working in or with large, global pharmaceutical organizations.

This position offers the opportunity to contribute meaningfully to Amgens global development portfolio while helping to establish and grow a high-impact Precision Medicine capability at Amgen India.