Neural Nexus – Data Lead

Career Category

Sales & Marketing Operations

Job Description

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. 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.

Neural Nexus – Data Lead

What you will do

Let’s do this. Let’s change the world. In this vital role of the Neural Nexus – Data Lead will have responsibilities to lead the overall Data strategy, infrastructures, and processes for our organization's innovative Neural Nexus (NN) - Generative AI and Automation platform. The incumbent will work closely with our Technology and AI&D organization to drive and deliver the successful design, implementation, rollout, and continuous evolution of this transformative program, ensuring its alignment with cross-functional teams and enterprise priorities to improve business impact.

The individual in this role will not merely drive and develop innovative data strategy and foundation; and will orchestrate a fundamental shift in how Amgen will adopt and harness the power of Neural Nexus and its core components – including Insights Command Center, Adaptive Resource Optimization, and Patient Intelligence Engine.

This position offers a unique opportunity to be at the forefront of AI adoption in a high-impact sector, addressing complex business challenges that merge advanced technology, pharmaceutical data science, and robust governance and agentic frameworks.

Flexible Commuter role to one of two US Sites, in Thousand Oaks, CA, OR Deerfield, IL. You will work on-site a minimum of 3 days a week.

We are seeking a strategic and technically adept Data Strategy Lead to drive the development of a robust data foundation that supports advanced AI capabilities, including Large Language Models (LLMs) and agentic frameworks. This role will focus on integrating structured and unstructured data, building scalable infrastructure, and delivering strategic leadership across data governance, AI readiness, and knowledge enablement.

Strategic Leadership & Roadmap Development for Data Strategy, Infrastructure & Processes for Neural Nexus.

• Define, articulate, and champion the strategic vision and long-term roadmap for the Neural Nexus data, infrastructure, and processes. This includes developing innovative and agile data infrastructure and processes, using automation and/or Agentic framework where possible, that are aligned with overarching NN key objectives and prioritized use cases
• Working closely with AI&D / Enterprise team to ensure compliance, integrity, accuracy, and reliability of all available internal and external data used in the commercialization of our brands, and providing strategic direction to the organization related to newly available data sources and acquisition strategy to meet the needs of NN
• Define and implement data governance framework and procedures for data ownership, lineage tracking, and stewardship to ensure traceability and accountability
• Working closely with CD&A Data Management team to assess and develop necessary data processes, including and not limited to QC, Master Data Management, Affiliation, etc. to ensure the highest standard of quality and are business ready
• Develop AI-Readiness Infrastructure – including and not limited to
• Develop frameworks to integrate structured data (e.g., transactional systems) and unstructured content (e.g., PDFs, emails, notes) into a unified data architecture that supports downstream AI and agentic capabilities
• Implement automated NLP-driven pipelines to extract, normalize, and align entities and relationships across data types to support scalable AI model development and analysis
• integration of structured and unstructured data and systems that are optimized for speed, relevance, and accuracy
• Determine appropriate real time data pipeline or schedule to continuously embed new data (ie. public domain vs CRM logs). The pipeline would also include versioning, logging, and monitoring to ensure reliability and interpretability
• De