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Senior Scientist - NGS Bioinformatics (Algorithm Development)
Amgen
Hyderabad, IND
Full-time
Senior · 6+ years experience
Onsite
Discovered 3 weeks ago
Free
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HOW MIGHT YOU DEFY IMAGINATION?
If you feel like you’re part of something bigger, it’s because you are.
At Amgen, our shared mission—to serve patients—drives all that we do.
It is key to our becoming one of the world’s leading biotechnology companies.
We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide.
It’s time for a career you can be proud of.
Full Job Posting
HOW MIGHT YOU DEFY IMAGINATION?
If you feel like you’re part of something bigger, it’s because you are. At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies. We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It’s time for a career you can be proud of.
What you will do
- The Bioinformatician – NGS (Algorithm Development) will support Large Molecule Discovery by designing, implementing, and optimizing computational methods for analysis of complex next-generation sequencing datasets. This role will focus on developing novel algorithms and analytical approaches for tasks such as short-read and long-read variant calling, clustering, sequence classification, and antibody design support.
- Working closely with bioinformatics principal scientists, software engineers, data scientists, and laboratory scientists, this individual will help evaluate and refine bioinformatic algorithms that turn sequencing data into actionable biological insight. The role combines scientific problem-solving, statistical analysis, and software development, and is well suited for someone who enjoys advancing new computational approaches in a research setting.
- In this role, your core responsibilities include:
- Develop and optimize computational methods for NGS analysis, including short- and long-read variant calling, clustering/de-duplication, immune repertoire analysis, assembly, and sequence classification.
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