Data Scientist

Overview

Serve as a core data science expert for AI-enabled capabilities within Amgen's Global Supply Chain Data & Analytics team. Design, develop, evaluate, deploy, and continuously improve AI assistants, agentic AI capabilities, and advanced analytics solutions supporting the analytics ecosystem.

What you'll do

• Serve as the data science technical lead and subject matter expert for assigned AI-enabled capabilities across analytics capabilities.
• Partner with product owners and supply chain stakeholders to translate business problems into prioritized AI and analytics use cases, technical approaches, success measures, and delivery plans.
• Design, develop, evaluate, and enhance GenAI and agentic AI solutions using large language models, retrieval-augmented generation, semantic search, prompt engineering, and multi-agent workflows.
• Establish evaluation and monitoring approaches for AI solutions, including accuracy, relevance, robustness, safety, user feedback, and appropriate human review.
• Apply machine learning, statistical modeling, and time-series analysis to supply chain use cases involving demand, supply, inventory, capacity, cost, risk, and operational performance.
• Collaborate with data engineers to develop trusted analytical datasets, reusable features, data quality checks, lineage, and documentation supporting AI and analytics products.
• Work with software engineering, architecture, platform, testing, and delivery partners to integrate data science capabilities into enterprise applications and support testing, deployment, production performance, and issue resolution.
• Provide technical guidance and reviews to data scientists, engineers, and delivery partners; coordinate dependencies and promote reusable approaches across connected products.
• Develop technical documentation, operating procedure, and contribute to technical reviews.
• Communicate findings, solution tradeoffs, risks, recommendations, and business impact to technical and non-technical stakeholders while contributing through the Agile delivery model and applicable AI and data governance processes.

What you'll need

• Master's degree and 1 to 3 years of Computer Science, IT or related field experience, or Bachelor's degree in data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or a related field, with 2 years of relevant experience, or Associate's degree in those fields, with 6 years of relevant experience.
• Hands-on experience with Python and SQL for data analysis, feature engineering, machine learning, natural language processing, and AI solution development.
• Experience designing or developing GenAI and large-language-model capabilities such as AI assistants, retrieval-augmented generation, embeddings, semantic search, prompt engineering, or agentic workflows.
• Strong foundation in machine learning, statistical analysis, exploratory data analysis, time-series methods, and model evaluation.
• Experience progressing data science or AI solutions from experimentation into production, including testing, version control, monitoring, and MLOps or LLMOps practices.
• Ability to work with large, complex datasets and collaborate on data modeling, data quality, lineage, and reusable analytical data pipelines.
• Demonstrated ability to translate business problems into technical approaches, independently lead a technical workstream, and communicate results clearly.
• Excellent critical-thinking, analytical, and problem-solving skills.
• Strong communication, collaboration, and stakeholder-management skills.
• Demonstrated ability to provide technical leadership and influence without formal authority.
• Ability to connect technical work to business outcomes and explain complex topics clearly.
• Strong presentation, knowledge-sharing, and mentoring skills.

Nice to have

• Experience with supply chain, manufacturing, or biotech analytics use cases such as demand and supply planning, inventory, capacity, cost, financial planning, or operational KPIs.
• Experience with cloud-based data and AI platforms, large-scale data processing, and integration of AI capabilities into enterprise applications.
• Understanding of responsible AI, AI governance, security, compliance, observability, and ongoing solution performance management.
• Experience supporting analytical or reporting products and working with cross-functional teams and delivery partners in an Agile or SAFe environment.
• Data Science, Artificial Intelligence, or Machine Learning Certification (Preferred).
• Cloud or Data Platform Certification (Optional).

Details

• Location: United States.
• Work mode: Remote.