Sr. Data Scientist – AI Driven Operations Research

Amgen Inc. (IR); Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Amgen India is seeking a highly analytical Sr. Data Scientist - AI Driven Operations Research to apply operations research, digital twin modeling, simulation, optimization, and analytics across drug development and supply chain operations.

The role emphasizes scalable analytical solution development, uncertainty handling, and collaboration with diverse teams to drive strategic decision-making in a GMP context.

Qualifications

• MS or PhD in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Data Science, or related field.
• Experience with digital twin platforms or simulation tools such as AnyLogic, Simio, Arena or similar.
• Experience with optimization solvers like Gurobi, CPLEX, OR-Tools.
• Strong Python programming for analytical application development.
• Experience building production-grade analytical software and data-driven apps.
• Familiarity with SQL and enterprise data architectures; knowledge of pharma compliance is a plus.
• Exposure to ML, predictive analytics, or AI-enabled decision systems.

Responsibilities

• Design and implement advanced analytical models using OR techniques including MILP, DES, Monte Carlo, and stochastic methods.
• Build scalable decision-support tools for scenario analysis and planning across Global Supply Chain.
• Analyze supply chain resilience and reliability to improve service levels and efficiency.
• Develop digital twin capabilities combining simulation, optimization, and ML for clinical supply chain operations.
• Architect and maintain modular Python-based analytics applications with strong engineering practices.
• Leverage AI-assisted coding and analytics to accelerate development and improve code quality.
• Collaborate with product, data, and technology teams to deliver data-driven solutions aligned with standards.

Skills

Operations Research

Python

Advanced modeling

Data analytics

Optimization

Simulation

Machine learning basics

Education

MS or PhD in quantitative field (OR/IE/Math/CS/Data Science)

Tools

AnyLogic

Simio

Arena

Gurobi

CPLEX

OR-Tools

SQL

Job description

Career Category Supply Chain Job Description

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.
• Supply chain performance and resilience analytics: Analyze supply chain performance under uncertainty and provide data-driven recommendations to improve service levels, operational efficiency, risk mitigation, and supply chain resilience.
• Optimization, simulation, and digital twin development: Support the development and deployment of enterprise digital twin capabilities for clinical supply chain operations, combining simulation, optimization, and machine learning techniques to enhance decision intelligence.
• Analytical application development: Architect, develop, and maintain modular Python-based analytics, optimization, and simulation applications with strong engineering practices for maintainability, testing, performance, and scalability.
• AI-assisted analytics and development: Leverage AI-assisted coding, analytics, and productivity tools to accelerate development, improve code quality, and enhance analytical solution delivery.
• Technology evaluation and learning agility: Explore emerging technologies, digital twin platforms, optimization solvers, simulation tools, and analytical methods applicable to clinical supply chain and operational decision-making.
• Technical standards and reusable frameworks: Contribute to technical standards, reusable modeling frameworks, simulation patterns, optimization methods, and analytics best practices across the organisation.
• Cross-functional collaboration and stakeholder partnership: Work closely with product teams, business teams, technology teams, data engineering teams, architecture teams, stakeholders, and subject‑matter experts to deliver practical, scientific, data‑driven solutions aligned with enterprise standards.
• Communication and decision translation: Communicate technical concepts, model assumptions, analytical findings, uncertainty, limitations, and implementation tradeoffs clearly to both technical and non-technical audiences.

Preferred Qualifications

• Advanced degree (MS or PhD preferred) in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Data Science, or related quantitative field.
• Experience with digital twin platforms or simulation tools such as AnyLogic (preferred), Simio, Arena, or similar technologies
• Experience with Optimization solvers (Gurobi, CPLEX, OR-Tools, etc.)
• Strong programming experience in Python for analytical application development.
• Experience building production-quality analytical software and data-driven applications.
• Familiarity with SQL, data engineering concepts, and enterprise data architecture
• Knowledge of inventory management, demand planning, production planning, or logistics optimization.
• Familiarity with pharma or life sciences compliance requirements (GxP, HIPAA) is a plus.
• Exposure to machine learning, predictive analytics, or AI-enabled operational decision systems.

Amgen is committed to unlocking the potential of biology for patients suffering from serious illnesses by discovering, developing, manufacturing and delivering innovative human therapeutics. This approach begins by using tools like advanced human genetics to unravel the complexities of disease and understand the fundamentals of human biology. Amgen focuses on areas of high unmet medical need and leverages its biologics manufacturing expertise to strive for solutions that improve health outcomes and dramatically improve people's lives. A biotechnology pioneer since 1980, Amgen has grew to be one of the world's leading independent biotechnology companies, has reached millions of patients around the world and is developing a pipeline of medicines with breakaway potential. For more information, visit www.amgen.com and follow us on www.twitter.com/amgen