Data Scientist

About The Role

The Global Quality Analytics and Innovation team at Amgen is at the forefront of digital transformation and innovation within the Quality organization. This team leverages cutting-edge technologies like automation, artificial intelligence (AI), and generative AI to drive end-to-end quality transformation. We are seeking a motivated and experienced Data Scientist with specialized expertise in Generative AI, Large Language Models (LLMs), and MLOps. A solid understanding of Quality principles in regulated environments, such as GxP, is essential. In this role, you will be instrumental in designing, developing, and deploying scalable AI/ML solutions to foster innovation, enhance efficiency, and ensure regulatory compliance across the organization. You will collaborate closely with diverse cross-functional teams, including software engineers, data engineers, business stakeholders, and quality professionals, to deliver AI-driven capabilities that align with strategic business objectives. The ideal candidate is an analytical thinker possessing deep technical knowledge, excellent communication skills, and the ability to thrive in a dynamic, agile work environment.

Key Responsibilities

• Design, build, and deploy generative AI and LLM-based applications utilizing frameworks such as LangChain, LlamaIndex, and others.
• Develop reusable and effective prompts for LLMs including OpenAI GPT-4, Anthropic Claude, and similar models.
• Create and maintain robust evaluation metrics and frameworks for prompt engineering.
• Perform data quality assessments, data cleansing, and ingest unstructured documents into vector databases.
• Build retrieval algorithms for identifying relevant data to support LLMs and AI applications.
• Ensure AI/ML development adheres to GxP and other regulatory standards, promoting a strong Quality culture.
• Partner with global and local teams to support regulatory inspection readiness and advance future AI technological capabilities.
• Communicate insights and findings to team members within an Agile (SAFe) framework.

Preferred Qualifications

• Master's degree and 2-4 years of experience in Software Engineering, Data Science, or ML Engineering.
• Proven experience in developing and deploying LLM applications.
• Strong foundational knowledge of ML algorithms, data science workflows, and Natural Language Processing (NLP).
• Expertise in Python and ML libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Familiarity with MLOps tools including MLflow, CI/CD pipelines, and version control systems.
• Experience with cloud platforms (AWS, Azure, GCP) and tools like Spark and Databricks.
• Understanding of RESTful APIs and frameworks like FastAPI.
• Experience with Business Intelligence (BI) and visualization tools such as Tableau, Streamlit, and Dash.
• Knowledge of GxP compliance and experience working within regulated environments.
• Excellent communication skills with the ability to articulate complex topics to varied audiences.
• High degree of initiative, self-motivation, and the capacity to work effectively in global teams.