MDM Data Scientist

ABOUT AMGEN 

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. 

ABOUT THE ROLE 

Role Description: 

We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgen’s Enterprise Data Management team. As part of 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. To succeed in this role, the candidate must have strong AI/ML, Data Science, GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like (PySpark/PyTorch, TensorFlow, LLM, Autogen, Hugging FaceVectorDB, Embeddings, RAGs etc), along with knowledge of MDM (Master Data Management) 

Roles & Responsibilities:  

• Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and 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 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: 

• Master’s degree with 4 - 6 years of experience in Business, Engineering, IT or related field  OR  

• Bachelor’s degree with 6 - 9 years of experience in Business, Engineering, IT or related field  OR 

• Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field 

Functional Skills: 

Must-Have Skills: 

• 6+ 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