Career Category Information Systems Job Description As a Senior Data Scientist, you will build and model digital product and platforms that bring Amgen’s AI/ML and GenAI solutions to life. This role has to collaborate with Amgen’s Technical Architect, Product Manager, UX designers, and Back-end engineers to design secure, scalable, and user-centric products that accelerate discovery, manufacturing, and commercial analytics, corporate functions products Key Responsibilities Strong experience with statistics and machine learning, including deep learning, natural language processing (NLP) and, experience in building cloud-scale systems and working with open-source stacks for data Experiment with large language models (LLM), Artificial intelligence (AI) for code or related fields, Generative AI, Foundational Models, Supervised and Unsupervised Learning Collaborate with cross-functional teams to understand the requirement and design solutions that meet business needs. Also with Data Architects, Business SMEs, and Technical Architect to design and develop to meet fast-paced business needs. Explore new tools and technologies that will help rapid development of solutions Participate in sprint planning meetings and provide estimations on technical implementation  Embed responsible-AI and security-by-design controls Required Qualifications 5–12 years of experience in Data Science (eg: managing structured and unstructured data, applying statistical techniques and reporting results) Doctorate or Master's or Bachelor's in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science or a related field Leverage cloud platforms (AWS preferred) to build scalable and efficient solutions  Strong background in Deep Learning, Machine Learning, NLP, Data Mining. Excellent communication and stakeholder management skills. Preferred Skills Experience in Generative AI, Foundational Models, LLM's, Feature Engineering, Selection & Extraction, BI & Automation, Predictive Modelling, Data Visualization, CNN, RNN, GNN, Transformers, Exploratory Data Analysis Familiarity with Python packages (Pytorch, TensorFlow, Hugging FaceScikit-learn, Pandas, NumPy, Matplotlib, Cloud Vision API, RAG, TensorBoard, OpenCV,NLTK)), programming languages ( C, C++, Java, CUDA,SQL, NoSQL, PHP, HTML, JS, CSS etc.) Prior exposure to pharma / life sciences AI environments is preferred. Strong understanding of Responsible AI and model validation principles. .