Sr. Data Scientist – AI Driven Operations Research

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 highly analytical and technically strong Sr. Data Scientist – AI Driven Operations Research to join our team. This role focuses on applying operations research, digital twin modeling, simulation, optimization, and advanced analytics to solve complex clinical and commercial supply chain challenges across drug development, manufacturing, distribution, and patient delivery operations.

The ideal candidate combines strong quantitative modeling expertise with hands-on software engineering capabilities to develop scalable, production-ready analytical solutions that support strategic and operational decision-making under uncertainty.

ROLES & RESPONSIBILITIES

Responsibilities will include, but are not limited to:

• Operations research and advanced modeling: Design and implement advanced analytical models using operations research techniques such as Mixed Integer Linear Programming, Discrete Event Simulation, Monte Carlo simulation, stochastic modeling, and decision analysis under uncertainty.

• Decision-support and scenario analysis: Build scalable decision-support tools for scenario analysis, operational planning, resilience assessment, and strategic tradeoff evaluation across Global Supply Chain use cases.