Principal Data Scientist

** Join Amgen's Mission of Serving Patients*
* At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.

Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas
-Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

** Principal Data Scientist*
* ** What you will do*
* Let's do this. Let's change the world. In this vital role you will play a key part in designing, developing, and deploying scalable AI/ML solutions and agentic systems to drive innovation, efficiency, and regulatory compliance across the organization.

You will collaborate with multi-functional teams, including software engineers, data engineers, business partners, and quality professionals to design and implement responsible and ethical AI-driven capabilities that support strategic business objectives.

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** Innovation & Research Translation** :
Stay at the forefront of AI/ML advancements-especially in the agentic AI and knowledge graph spaces-and translate emerging techniques into enterprise-ready applications.

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** Agentic System Design & Innovation** :
Architect and deploy agent-based and multi-agent AI/ML systems to enhance automation, decision-making, and operational efficiency, leveraging modern frameworks and GenAI capabilities.

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** Data Excellence & MLOps Governance** :
Champion robust data science practices and develop scalable, auditable MLOps pipelines. Enforce standards for versioning, testing, monitoring, documentation, and security to ensure high-quality model lifecycle management.

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** Enterprise Integration & Cross-Functional Alignment:
** Partner with technology, product, and business team members to align AI initiatives with enterprise goals. Ensure solutions are traceable, interoperable, and embedded within Amgen's digital Quality ecosystem.

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** Responsible & Ethical AI:
** Embed principles of ethical AI-including fairness, transparency, privacy, and explain-ability-into the design and deployment of AI/ML solutions. Ensure alignment with Amgen's Quality and Compliance standards and global regulatory frameworks.

** What we expect of you*
* We are all different, yet we all use our unique contributions to serve patients. The professional we seek is a go getter with these qualifications.

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* Basic Qualifications:

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* Doctorate degree and 2 years of  
** Data Science, Software/ML Engineering,
** experience

OR

Master's degree and 4 years of  
** Data Science, Software/ML Engineering,
** experience

OR

Bachelor's degree and 6 years of  
** Data Science, Software/ML Engineering,
** experience

OR

Associate's degree and 10 years of  
** Data Science, Software/ML Engineering,
** experience

OR

High school diploma / GED and 12 years of  
** Data Science, Software/ML Engineering,
** experience

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* Preferred Qualifications:

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* + Demonstrated success providing technical leadership to teams delivering AI, machine learning, generative AI, analytics, or intelligent automation products in production.

+ Experience delivering AI-enabled solutions within GxP-regulated biotechnology, pharmaceutical, healthcare, or life-sciences environments.

+ Strong understanding of GxP principles, data integrity, computer-system validation, risk-based validation, change control, and regulated model lifecycle management.

+ Proven expertise designing and implementing AI, machine learning, and generative AI applications, including agent-based or multi-agent systems.

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Experience with frameworks and patterns such as Lang Chain, Lang Graph, Llama Index, retrieval-augmented generation, GraphRAG, vector search, and knowledge graphs.

+ Advanced proficiency in Python and common machine-learning libraries such as PyTorch, Tensor Flow,…