Sr. Data Scientist – Analytics Applications & Decision Support

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, Global Supply Chain is seeking a Sr. Data Scientist – Analytics Applications & Decision Support to rapidly prototype, build, and deliver user-facing analytics applications, interactive decision-support tools, and visual analytics experiences for clinical and commercial supply chain processes.

This role will combine data science, front-end analytics application development, visualization, cloud technologies, API integration, and product-oriented delivery. The ideal candidate is a versatile technical data scientist who can translate business concepts into intuitive working solutions, build interactive user experiences, contribute across front-end and back-end components when needed, and create practical tools that improve supply chain visibility, decision-making, and operational execution.

ROLES & RESPONSIBILITIES

Responsibilities will include, but are not limited to:

Rapid prototyping and analytics application development: Quickly translate business concepts, scientific questions, and product ideas into working prototypes, interactive analytics applications, and user-facing decision-support tools.

Decision-support and visual analytics delivery: Build a wide range of data and analytics solutions, from descriptive to prescriptive analytics, including dashboards, visual analytics, interactive interfaces, and decision-support tools.

Front-end analytics application development: Design and build intuitive user interfaces, visual workflows, and interactive components for analytics applications using modern front-end and visualization technologies.

Technical documentation and solution clarity: Create and maintain clear technical documentation, including solution design, software architecture, data flows, API specifications, implementation details, and key design decisions.

Technical problem-solving and delivery execution: Identify, troubleshoot, and resolve technical challenges effectively while balancing speed, quality, maintainability, risk, and long-term scalability.

Technology evaluation and learning agility: Stay current with technology trends, cloud capabilities, analytics application frameworks, visualization tools, front-end technologies, and engineering practices; assess options and make informed technology recommendations based on business value, technical fit, and implementation impact.

Product and module ownership: Develop a strong understanding of the overall product, its modules, dependencies, data flows, user workflows, and interface touchpoints while serving as a technical expert for assigned components or solution areas.

Cross-functional collaboration and stakeholder partnership: Work closely with product teams, business teams, architecture teams, technology teams, UX partners, data teams, stakeholders, and subject-matter experts to deliver practical, scientific, user-centered, data-driven solutions aligned with enterprise standards.

Requirements translation and Agile delivery: Synthesize business, scientific, user experience, and technical inputs into prioritized features, user stories, acceptance criteria, and delivery plans; actively participate in Agile ceremonies, including sprint planning, backlog refinement, estimation, demos, and retrospectives.

FUNCTIONAL SKILLS

Must-Have Skills

Hands-on experience with cloud services and well-architected cloud design principles, with the ability to evaluate tradeoffs across different cloud solution options.

Experience developing dashboards, visual analytics, interactive decision-support tools, or user-facing analytics applications using technologies such as React, JavaScript/TypeScript, Posit/Shiny, Plotly Dash, Streamlit, Power BI, Tableau, or similar tools.

Hands-on experience building analytics applications that include user interfaces, APIs, data pipelines, and integration with structured or unstructured data sources.

Strong proficiency in Python and SQL, with working knowledge of JavaScript/TypeScript, React, Node.js, REST or GraphQL APIs, and SQL/NoSQL databases.

Ability to translate business, scientific, and analytical requirements into intuitive user experiences, visual workflows, dashboards, and interactive decision-support interfaces.

Experience applying analytics, data science, visualization, or decision-support tools to supply chain use cases, with a solid understanding of supply chain management principles and complex business problem-solving.

Familiarity with pharma or life sciences compliance requirements, including GxP, HIPAA, or related expectations, is a plus.