AI Data Scientist

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the worlds toughest diseases, and make peoples lives easier, fuller, and longer. We discover, develop, manufacture, and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains at the cutting edge of innovation, using technology and human genetic data to push beyond what is known today.

ABOUT THE ROLE

You will play a critical role in advancing Amgens Operations Transformation and Digital Strategy by designing and delivering next-generation AI solutions that modernize how data, knowledge, and content are created, connected, governed, and consumed across the enterprise, in collaboration with the Operations AI Transformation Team.

This role is focused on applying Generative AI, agentic AI, integrated data, and semantic technologies to solve complex business problems in a highly regulated environment. The AI Data Scientist will help shape and scale AI-enabled solutions that support enterprise transformation, with particular emphasis on regulatory, operational, and data-centric use cases. This role will contribute to initiatives that combine modern AI capabilities with structured content, knowledge graphs, and interoperable data models to enable intelligent automation, improved decision-making, and new ways of working.

This is an individual contributor role for a technically strong and strategically minded AI practitioner who can move from concept to proof of value and from prototype to scalable implementation while maintaining a strong commitment to responsible AI, compliance, and continuous improvement.

Role Description

The AI Data Scientist is responsible for designing, developing, and scaling AI-driven solutions that combine Generative AI, agentic AI, semantic data, and enterprise data platforms to create measurable business value. This role requires deep technical expertise, strong business engagement, and the ability to translate ambiguous business opportunities into production-oriented AI products and capabilities.

With a focus on pharmaceutical and operational data domains, the role involves applying data science, ontology-based modeling, knowledge graph methods, and modern AI technologies to build intelligent systems that can reason over interconnected data, generate insights, and automate knowledge-intensive tasks. The role will work across structured and unstructured data, leveraging AWS, Databricks, OpenAI APIs, AWS Bedrock, and related platforms to deliver scalable and compliant AI solutions.

This role will also help establish best practices in AI, support transformation initiatives through experimentation and applied innovation, and promote a culture of continuous improvement in AI product delivery and business adoption.

Roles Responsibilities

• Design, develop, and deploy AI solutions using Generative AI, large language models, and agentic AI patterns to address high-value business and operational challenges.
• Build intelligent solutions that combine structured and unstructured data, semantic data models, and knowledge graph capabilities to improve automation, search, insight generation, and decision support.
• Develop and scale proof-of-concept solutions in Python and transition them into robust, enterprise-ready AI products for broader organizational use.
• Apply SQL and other data transformation techniques to analyze, integrate, and prepare data from multiple enterprise sources.
• Collaborate with business stakeholders, product teams, data engineers, architects, and domain experts to identify AI use cases and translate business requirements into scalable technical solutions.
• Integrate FAIR data principles and data-centric design practices with AI to promote interoperability, discoverability, and governance of data assets.
• Leverage AWS services and cloud best practices, including AWS Bedrock, to design scalable, secure, and maintainable AI solutions.
• Develop AI-enabled applications using OpenAI APIs, foundation model platforms, and enterprise AI tooling in alignment with business and technical standards.
• Utilize Databricks and associated data/AI workflows to support experimentation, model development, and scalable deployment patterns.
• Ensure alignment with Responsible AI, security, privacy, and compliance expectations, including familiarity with emerging AI regulato…