ABOUT AMGEN
Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s 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 leadership role in advancing Amgen’s Operations Transformation and Digital Strategy (OTDS) by guiding the design and delivery of next-generation AI solutions that modernize how data, knowledge, and content are created, connected, governed, and consumed across the enterprise, in collaborate with the Operations AI Transformation Team.
This role focuses on scaling the application of Generative AI, agentic AI, integrated data, and semantic technologies across high-impact business domains. As an AI Data Scientist Manager, you will lead a team of AI practitioners to deliver enterprise-grade AI solutions while driving alignment across business stakeholders, product teams, and technology partners.
You will be responsible for shaping strategy, driving execution, and ensuring the successful delivery of AI-enabled transformation initiatives, particularly within regulatory, operational, and data-centric use cases. This role combines strong technical depth with people leadership, product thinking, and the ability to influence at scale in a highly regulated environment.
Role Description
The AI Data Scientist Manager is responsible for leading a team of AI data scientists in 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 a balance of technical expertise, people leadership, and strategic thinking, with accountability for both delivery and team development. You will oversee the end-to-end lifecycle of AI solutions—from ideation and prototyping to production deployment, while ensuring alignment with enterprise standards for Responsible AI, compliance, and data governance.
With a focus on pharmaceutical and operational data domains, this role involves guiding the development of intelligent systems that leverage knowledge graphs, interoperable data models, and modern AI technologies. You will work across structured and unstructured data ecosystems using platforms such as AWS, Databricks, OpenAI APIs, and AWS Bedrock to deliver scalable and compliant solutions.
This role also serves as a thought leader within OTDS, helping to define best practices, influence AI strategy, and foster a culture of innovation, continuous improvement, and transformation.
Roles & Responsibilities
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Lead and manage a team of AI Data Scientists (approximately 4–6 direct reports), providing mentorship, coaching, and performance management.
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Define team priorities, manage scope, and ensure successful delivery of AI initiatives aligned with OTDS transformation goals.
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Design and oversee development of AI solutions using Generative AI, large language models, and agentic AI patterns.
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Guide the development of intelligent systems that combine structured and unstructured data, semantic models, and knowledge graphs.
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Ensure successful transition of solutions from proof-of-concept to scalable, enterprise-ready AI products.
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Provide technical leadership in Python-based development, SQL-based data transformation, and AI system design.
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Collaborate with business stakeholders, product teams, architects, and engineering partners to define and deliver high-impact AI use cases.
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Drive adoption of FAIR data principles, data-centric design, and semantic interoperability across solutions.
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Oversee use of AWS services and cloud best practices, including AWS Bedrock, to ensure scalable and secure architectures.
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Guide development of AI-enabled applications leveraging OpenAI APIs and foundation model platforms.
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Ensure effective use of Databricks and enterprise data platforms for scalable AI development and deployment.
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Establish and enforce standards for Responsible AI, model governance, security, and compliance, including awareness of frameworks such as the EU AI Act.
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Act as a key liaison between OTDS leadership and cross-functional stakeholders to align priorities and drive transformation outcomes.
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Facilitate strategic discussions and working sessions to align on AI vision, roadmap, and value realization.
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Promote a culture of continuous improvement, innovation, and operational excellence across the team.
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Stay current with advancements in AI, agentic architectures, and regulatory expectations, and guide the team in applying them effectively.
Basic Qualifications and Experience
Doctorate Degree OR
Master’s degree with 6 to 8 years of experience in Data Science, Artificial Intelligence, Computer Science, Information Science, or related field OR
Bachelor’s degree with 8 to 10 years of experience in Data Science, Artificial Intelligence, Computer Science, Information Science, or related field
Plus: Demonstrated experience leading or mentoring teams in a technical environment
Functional Skills
Must-Have Skills
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Strong experience leading and developing high-performing technical teams.
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Deep expertise in Generative AI, large language models, and agentic AI applications.
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Proficiency in Python for AI solution development and scaling.
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Strong working knowledge of SQL for enterprise data integration and analysis.
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Experience with AWS cloud services and well-architected design principles, including AWS Bedrock.
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Experience with OpenAI APIs and enterprise AI solution development.
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Hands-on experience with Databricks or similar data and AI platforms.
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Strong understanding of enterprise data ecosystems and integrated data architectures.
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Experience with knowledge graph technologies (e.g., Stardog, GraphDB) and semantic data approaches.
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Strong understanding of FAIR data principles and their enterprise application.
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Ability to translate business strategy into scalable AI solutions and execution roadmaps.
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Strong understanding of Responsible AI principles, governance, and compliance requirements.
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Familiarity with AI regulatory considerations, including concepts aligned with the EU AI Act.
Good-to-Have Skills
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Experience in pharmaceutical or life sciences environments, particularly in regulatory or operational domains.
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Familiarity with regulatory data, submission processes, and compliance frameworks.
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Knowledge of machine learning and deep learning techniques supporting GenAI use cases.
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Experience integrating data across clinical, manufacturing, quality, or regulatory systems.
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Familiarity with FHIR, IDMP, or similar healthcare data standards.
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Experience scaling AI solutions into enterprise products and platforms.
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Exposure to structured content management and AI-driven content automation.
Soft Skills
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Strong leadership, coaching, and team development capabilities.
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Excellent communication and stakeholder management skills across technical and business audiences.
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Strategic thinking with the ability to align AI initiatives to enterprise transformation goals.
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Strong analytical and problem-solving skills in complex, regulated environments.
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Ability to manage ambiguity and drive clarity across multiple initiatives.
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Demonstrated ability to influence without authority and build cross-functional alignment.
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Strong customer- and product-oriented mindset.
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Passion for continuous improvement, innovation, and transformation.
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High level of ownership and accountability for both team outcomes and business impact.
EQUAL OPPORTUNITY STATEMENT
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 with 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 an accommodation.
