MDM Data Science Manager

We areseekingan accomplished and visionaryData Scientist/GenAILead to join Amgens Enterprise Data Management team.

As MDM Data Science/Manager, you will lead the design, development, and deployment of 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. To succeed in this role, the candidate must have strongAI/ML,Data Science,GenAIexperience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must haveAI/ML,data science andGenAIexperience on technologies like (PySpark/PyTorch, TensorFlow, LLM,Autogen, HuggingFaceVectorDB, Embeddings, RAGsetc), along with knowledge of MDM (Master Data Management)

Roles & Responsibilities:

• Drive development of enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face.
• Architect 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 like Informatica and 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:

• Masters degree with 8 - 10 years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR
• Bachelors degree with 10 - 14 years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR
• Diploma with 14 - 16 years of hands-on experience in Data Science, AI/ML technologies, or related technical domains

Functional Skills:

Must-Have Skills:

• 10+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions.
• Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models.
• Strong programming background with Python, PySpark, and experience in 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 like Django, FastAPI, and DataBricks.
• Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices.
• Guide the team on development activities and lead the solution discussions
• Must have core technical capabilities in GenAI, 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