About Amgen

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.

About The Role

Role Description:

As an Associate Data Scientist, you will help build next-generation AI-powered platforms that transform how commercial, contracting, and patient access strategies are designed and executed across the US Value & Access organization. Our AI portfolio includes AI copilots, intelligent contract systems, anomaly detection engines, and real-time decision platforms that directly impact how Amgen serves patients and partners.

In this role, you will work on production-grade AI systems, contributing to the development of scalable, intelligent solutions that integrate structured and unstructured data, power decision-making, and deliver measurable business impact. You will collaborate with senior data scientists, engineers, and business partners to bring cutting-edge GenAI, LLM, and ML solutions from prototype to production.

Roles & Responsibilities:

You will contribute to one or more of the following high-impact areas:

AI Copilots & Agents: Build LLM-powered assistants, implement prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows and related applications
Intelligent Document & Contract AI: Extract, classify, and query insights from unstructured documents (contracts, policies, SOPs); build NLP pipelines for semantic search and summarization
Data & AI Platforms: Work on data ingestion, transformation, and feature engineering pipelines; contribute to scalable AI/ML infrastructure
Real-time AI Systems: Build APIs, dashboards, and backend services that power AI-driven insights for end users
Analytics & Decision Engines: Develop anomaly detection models (e.g., claims, pricing, Gross-to-Net); build forecasting and optimization models to support commercial decisions
Collaborate with cross-functional technical teams to translate business needs into technical specifications, focusing on AI-driven automation and insights
Participate in code reviews, design discussions, and adopt best practices across MLOps and software engineering

Functional Skills:

Must-Have Skills:

Strong programming skills in Python, PySpark, and SQL
Solid understanding of Data Structures & Algorithms, OOP, and System Design fundamentals
Hands-on experience with core Machine Learning techniques (Regression, Classification, Clustering)
Working knowledge of NLP fundamentals (tokenization, embeddings, transformers)
Exposure to LLMs (OpenAI, HuggingFace, Anthropic, etc.) and prompt engineering / GenAI workflows
Experience with data manipulation libraries (Pandas, NumPy) and working with both structured and unstructured data
Familiarity with REST APIs and backend development basics
Mandatory hands-on experience with 2–3 real AI/ML projects
AI/GenAI: LLM-based chatbot with RAG (document Q&A), AI summarization tools, or agent-based multi-step reasoning systems
Engineering: Deployed ML models (API or web app), data pipelines (ETL/ELT)

Good-to-Have Skills:

Experience with RAG pipelines and vector databases (FAISS, Pinecone, Chroma, Weaviate)
Hands-on experience with LangChain, LlamaIndex, or agent frameworks (AutoGen, CrewAI)
Exposure to MLOps tools (Docker, CI/CD, MLflow, Kubeflow, Airflow)
Knowledge of time-series forecasting and anomaly detection techniques
Frontend basics (Streamlit, React) for building dashboards and demos
Familiarity with cloud platforms (AWS, Azure, or GCP)
Experience with Databricks for data analytics and ML workflows
Foundational understanding of the US pharmaceutical ecosystem, relevant datasets (e.g., claims, prescription data), and Patient Support Services offerings

Professional Certifications (optional):

Any AWS / Azure / GCP certification (preferred)
Any Python, Machine Learning, or GenAI certification (preferred)

Soft Skills:

Initiative to explore new technologies and alternate approaches to solving problems
Strong analytical and troubleshooting skills with the ability to break down complex problems
Excellent verbal and written communication skills
Ability to work effectively with global, virtual, cross-functional teams
High degree of curiosity, initiative, and self-motivation
Team-oriented mindset with a focus on collective goals
Ability to manage multiple priorities and learn quickly in a fast-paced environment

Basic Qualifications:

Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Engineering, or other STEM majors
2–6 years of hands-on experience in AI/ML, data science, or software engineering roles
Demonstrated portfolio of AI/ML projects (GitHub, publications, or production deployments)

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.

Associate Data Scientist - Value & Access Strategy