Sr. Data Scientist – Analytics Applications & Decision Support

Job description

Career Category Clinical Development 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, 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. .