Senior Manager - Data Sciences & AI

Career Category

Supply Chain

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 is known today.

ABOUT THE ROLE

Role Description

Global Supply Chain (GSC) is accountable for orchestrating end-to-end supply chain strategies and operations that ensure reliable, timely delivery of medicines to patients — powered by data, innovation, and enterprise-wide collaboration.

As part of our team expansion at Amgen India (AIN), GSC is seeking a Senior Manager - Data Sciences & Artificial Intelligence to lead a team of data scientists responsible for building scalable digital, data, and AI-enabled solutions for clinical and commercial supply chain processes. This multi-faceted team leader will build and establish a new group within AIN that combines people leadership, product ownership, client success, data science, supply chain modelling and AI engineering.

This role will be accountable for shaping a high-performing local team while also driving the delivery of high-impact digital capabilities for Global Supply Chain. This is a unique opportunity to help build a new footprint at AIN from the ground up and strengthen an industry leading capability with a track record in the digital transformation space at the intersection of supply chain management, data, modeling, and artificial intelligence.

ROLES & RESPONSIBILITIES

Responsibilities will include, but are not limited to:

• People leadership and line management: coaching, performance management, hiring input, workload prioritization, team health, and talent development.

• Technical leadership and cross-functional delivery: Guide data scientists, product owners, business partners, architecture teams, AI platform teams, data teams, and stakeholders through delivery decisions, dependencies, and tradeoffs.