About this role
Job title: Senior Data Scientist
About the Role 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 collaborates 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.
What You'll Do
- Design and develop cloud-scale systems and work with open-source stacks for data; apply statistics and machine learning including deep learning, NLP, and generative AI.
- Experiment with large language models (LLMs), Generative AI, Foundational Models, supervised and unsupervised learning; embed responsible-AI and security-by-design controls.
- Collaborate with cross-functional teams to understand requirements and design solutions that meet business needs; coordinate with Data Architects, Business SMEs, and Technical Architects.
- Explore new tools and technologies to enable rapid development; participate in sprint planning and provide estimations on technical implementation.
What We're Looking For
- 6–12 years of experience in Data Science (managing structured and unstructured data, applying statistical techniques, reporting results).
- Advanced degree: Doctorate or Master's or Bachelor's in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field.
- Proficiency with cloud platforms (AWS preferred); strong background in Deep Learning, ML, NLP, Data Mining.
- Excellent communication and stakeholder management skills.
- Experience with Generative AI and LLMs; familiarity with Python packages (PyTorch, TensorFlow, Hugging Face, Scikit-learn, Pandas, NumPy, Matplotlib, Cloud Vision API, RAG, TensorBoard, OpenCV, NLTK) and programming languages (C, C++, Java, CUDA, SQL, NoSQL, PHP, HTML, JavaScript, CSS).
- Preferred: prior exposure to pharma / life sciences AI environments; strong understanding of Responsible AI and model validation principles.
Nice to Have
- Prior exposure to pharma / life sciences AI environments is preferred.