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Senior Scientist – Scientific Data & ML Enablement

Amgen

Senior Scientist – Scientific Data & ML Enablement

full-timePosted: Jul 29, 2026Updated: Aug 28, 2026India - Hyderabad

Job Description

Career CategoryResearchJob DescriptionHOW 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.Senior Scientist – Scientific Data & ML Enablement (Large Molecule Discovery Informatics)LiveWhat you will doIn this vital role, you will enable AI-driven research across Large Molecule Discovery by designing, managing, and optimizing the scientific datasets that power machine learning applications. This role will focus on transforming complex biological and experimental data into reliable, reusable, and ML-ready assets that support model development, deployment, and long-term scalability.Working at the intersection of data engineering, scientific informatics, and machine learning, this individual will partner with scientists, AI/ML researchers, software engineers, and data platform teams to ensure that discovery data is structured and accessible for advanced analytics and AI applications. The successful candidate will help establish scalable data models, metadata frameworks, and transformation pipelines that improve data quality, consistency, and reuse across the LMD ecosystem.This role is ideal for someone who enjoys solving complex scientific data challenges and is passionate about building the data foundations necessary to accelerate AI-enabled drug discovery.Core responsibilities include:• Design and maintain scalable data models supporting machine learning, analytics, and scientific research workflows• Create and maintain ML-ready datasets for model training, validation, and deployment• Partner with scientists to translate experimental workflows into effective data structures and reusable datasets• Implement metadata, lineage, and governance practices that improve data quality, traceability, and reuse• Develop standardized approaches for biological, assay, sequencing, and protein engineering datasets• Design and optimize data transformation workflows supporting machine learning and analytics use cases• Support integration of data from multiple scientific systems and repositories• Collaborate with scientists, bioinformaticians, engineers, and AI teams to accelerate AI-enabled discovery researchWinWhat we expect of youBasic Qualifications:Doctorate degree PhD with 5+ years of relevant expOrMaster’s degree and 8+ years of directly related experienceOrBachelor’s degree and 10+ years of directly related experiencePreferred Qualifications:• Experience designing data models supporting scientific, analytical, or machine learning applications• Strong proficiency in SQL, Python, and modern data engineering platforms• Experience creating datasets for machine learning, predictive modeling, or advanced analytics• Understanding of metadata, data lineage, governance, and reproducibility concepts• Experience working with biotechnology, pharmaceutical, genomics, or life science datasets• Familiarity with scientific data platforms and research informatics environments• Strong analytical, communication, and cross-functional collaboration skillsThriveWhat you can expect of usAs we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts.A discretionary annual bonus program, or for field sales representatives, a sales-based incentive planStock-based long-term incentivesAward-winning time-off plans and bi-annual company-wide shutdownsFlexible work models, including remote work arrangements, where possibleApply nowfor a career that defies imaginationObjects in your future are closer than they appear. Join us.careers.amgen.comApplication deadlineAmgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation..

Locations

  • India - Hyderabad

Required Qualifications

  • Doctorate degree PhD with 5+ years of relevant exp (experience, 5 years)
  • Master’s degree and 8+ years of directly related experience (experience, 8 years)
  • Bachelor’s degree and 10+ years of directly related experience (experience, 10 years)

Responsibilities

  • In this vital role, you will enable AI-driven research across Large Molecule Discovery by designing, managing, and optimizing the scientific datasets that power machine learning applications. This role will focus on transforming complex biological and experimental data into reliable, reusable, and ML-ready assets that support model development, deployment, and long-term scalability.
  • Working at the intersection of data engineering, scientific informatics, and machine learning, this individual will partner with scientists, AI/ML researchers, software engineers, and data platform teams to ensure that discovery data is structured and accessible for advanced analytics and AI applications. The successful candidate will help establish scalable data models, metadata frameworks, and transformation pipelines that improve data quality, consistency, and reuse across the LMD ecosystem.
  • This role is ideal for someone who enjoys solving complex scientific data challenges and is passionate about building the data foundations necessary to accelerate AI-enabled drug discovery.

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