Senior Manager - Data Sciences & AI

Amgen; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Amgen seeks a Senior Manager - Data Sciences & AI to lead a new group within AIN, uniting people leadership, product ownership, client success, data science, and AI engineering for Global Supply Chain. You will shape a local high-performing team and deliver high-impact digital capabilities across supply chain processes.

The role combines leadership with hands-on, pragmatic delivery, enabling innovation while ensuring security, compliance, and scalable architecture in a regulated life sciences

Qualifications

• Experience in pharma / life sciences with quality, compliance and data privacy expectations.
• Strong understanding of supply chain processes and data-driven decision making.
• Proven track record leading software, AI, or data engineering delivery teams.
• Experience operating in product, platform, data, analytics, or enterprise apps.
• Ability to translate business needs into scalable, secure technology solutions.
• Experience in Agile delivery and managing multiple priorities and stakeholders.
• Experience delivering end-to-end software from concept to production support.
• Ability to assess options, tradeoffs, costs, risk, and long-term value.

Responsibilities

• People leadership and line management: coaching, hiring input, and team health.
• Guide cross-functional teams through delivery decisions and tradeoffs.
• Partner with stakeholders to translate supply chain needs into scalable product solutions.
• Apply AI/ML and data engineering principles to build scalable capabilities.
• Build and operationalize AI capabilities with governance and safety considerations.
• Demonstrate leadership in AI, data science, and product practices with technical depth.
• Balance business needs with technical debt, delivery capacity, and risk.

Skills

Pharma / life sciences

Supply chain processes

Lead software / AI engineering teams

Product / platform / data environments

Agile delivery

End-to-end software delivery

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

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.

Role Description

We are 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, modelling, and artificial intelligence.

Roles & Responsibilities

• 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.
• Product ownership, domain translation, and client success: partner with subject-matter experts, business stakeholders, and technical teams to translate supply chain needs into scalable product solutions that deliver measurable outcomes.
• Data science and data engineering fluency: applying core principles of artificial intelligence, machine learning, data modelling, data quality, metadata, data lineage, and data pipelines to define solutions to complex problems.
• AI engineering and application delivery: building, integrating, evaluating, and operationalizing AI/ML capabilities, including context engineering, agents/workflows, evaluations, guardrails, and human‑centric designs.
• Learning agility and hands‑on technical credibility: demonstrating leading‑edge understanding of AI, semantic technologies, and product practices while retaining enough technical depth to prototype, review designs, challenge assumptions, and unblock teams.
• Pragmatic prioritization and delivery management: balancing business needs, technical debt, delivery capacity, risk, speed, dependencies, stakeholder expectations, and long‑term scalability across multiple projects.
• Enterprise architecture, quality, and compliance leadership: ensuring solutions are secure, reliable, maintainable, well‑documented, and aligned with enterprise architecture, operational standards, cybersecurity, data privacy, model governance, GxP, HIPAA, and other applicable life sciences compliance expectations.
• Innovation and engineering culture: fostering a culture of innovation, accountability, inclusion, continuous learning, technical curiosity, rapid prototyping, platform‑first thinking, and high‑quality delivery.

Functional Skills

Must‑Have Skills

• Experience in pharma, biotechnology, life sciences, regulated manufacturing, or GxP‑compliant technology environments with quality, compliance, data privacy, security, and documentation expectations.
• Strong understanding of supply chain processes.
• Demonstrated experience leading software engineering, AI engineering, data engineering, analytics, or technical delivery teams.
• Experience operating in product, platform, data, analytics, or enterprise application environments.
• Ability to translate business needs into scalable, secure, maintainable, and compliant technology solutions.
• Experience operating in Agile delivery environments and managing multiple priorities, projects, and stakeholder groups.
• Experience supporting end‑to‑end software delivery from concept through production stabilization and ongoing support.
• Ability to assess technology options, understand tradeoffs, and make sound recommendations based on business value, cost, risk, compliance, technical debt, delivery capacity, and long‑term impact.