Senior Manager – Data Sciences & Artificial Intelligence – Amgen

Are you ready to step into a high-impact leadership role as an Amgen AI Data Science Manager? A global biotechnology leader is expanding its footprint in India and looking for an exceptional visionary to join the Transformative Digital Capabilities (TDC) team in Hyderabad. In this position, you will drive Process Development (PD) and Operations digital transformation by building pragmatic digital solutions that bridge advanced computing with core biological and chemical sciences.

As an Amgen AI Data Science Manager, you will lead a newly formed group within Amgen India (AIN) that combines people leadership, product management, data engineering, and cutting-edge machine learning. You will work closely with global tech units to turn ambiguous, complex scientific challenges into highly scalable artificial intelligence products.

Responsibilities

1. People & Line Leadership: Provide ongoing coaching, performance management, hiring input, workload prioritization, and career development guidance to a talented engineering group.

2. Technical Guidance & Cross-Functional Collaboration: Guide data scientists, AI engineers, ontology specialists, and business partners through architecture decisions, cross-functional dependencies, and deployment tradeoffs.

3. Product Ownership: Map out a clear product vision, manage backlog prioritization, execute release planning, and establish rapid feedback loops to optimize client outcomes.

4. AI Engineering & Delivery: Oversee the operationalization of sophisticated AI/ML systems, including Retrieval-Augmented Generation (RAG), context engineering, autonomous agents, and human-centric UI/UX workflows.

5. Ontology & Graph Implementations: Define controlled vocabularies, taxonomies, semantic entity relationships, and graph data models to optimize corporate knowledge management.

Also Check: Senior Quality Engineer – Amgen

Required Qualifications and Technical Expertise

1. Experience: 8 to 12 years of core experience in data science, artificial intelligence engineering, or technical product management.

2. Leadership Track Record: Proven background in managing high-performing agile engineering teams under the Scaled Agile Framework.

3. Core Fluency: Deep domain proficiency in machine learning pipelines, data quality protocols, metadata lineage, and complex in silico modeling.

4. Semantic Technologies: Hands-on knowledge of entity resolution patterns, graph databases, and semantic query operations.

5. Domain Translation: Excellent learning agility and the technical credibility to review designs, challenge architecture assumptions, and prototype standalone modules alongside engineering teams.