MDM Data Scientist

We are seeking an accomplished and visionary Data Scientist/GenAI Developer to join Amgen's Enterprise Data Management team. As part of the MDM team, you will be responsible for designing, developing, and deploying Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. Important Note: To succeed in this role, candidates must possess strong AI/ML, Data Science, and GenAI experience along with MDM knowledge. Candidates with only MDM experience are not eligible for this role. Expected technical experience includes PySpark/PyTorch, TensorFlow, LLM, Autogen, Hugging Face, VectorDB, Embeddings, RAGs, etc., alongside knowledge of Master Data Management (MDM). Roles & Responsibilities Develop enterprise-level GenAI applications using LLM frameworks (e.g., Langchain, Autogen, Hugging Face). Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models and manage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms (e.g., Informatica, Reltio) to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience Master's degree with 4 - 6 years of experience in Business, Engineering, IT, or a related field OR Bachelor's degree with 6 - 9 years of experience in Business, Engineering, IT, or a related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT, or a related field Functional Skills Must-Have Skills 6+ years of experience in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools (e.g., Langchain, Autogen, Hugging Face, OpenAI APIs, embedding models). Strong programming background with Python, PySpark, and experience building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks (e.g., Django, FastAPI, DataBricks). Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Ability to guide the team on development activities and lead solution discussions. Core technical capabilities in GenAI and Data Science space. Good-to-Have Skills Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications Any ETL certification (e.g., Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams.