Back
Tier-1 brand, metro location, popular Data Scientist title, and broad full-stack analytics requirements increase competition.
Technical analytics skills transfer easily, but supply-chain and pharma compliance needs raise domain specificity.
No explicit years but multiple mandatory technical skills and domain experience make filters moderately strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Prototype and deliver user-facing analytics applications and interactive decision-support tools for clinical and commercial supply chain processes.
Develop front-end visualization components and back-end integrations including APIs and data pipelines to improve supply chain visibility and decision-making.
Own product modules and collaborate cross-functionally to translate requirements into prioritized, Agile-delivered features aligned with enterprise standards.
Hands-on experience with cloud services and architecting cloud solutions.
Proficiency in Python, SQL, and front-end technologies such as JavaScript/TypeScript, React; experience with analytics application frameworks like Posit/Shiny, Plotly Dash, Streamlit, Power BI, or Tableau.
Experience building analytics applications integrating user interfaces, APIs, and data pipelines with structured or unstructured data.
Work Experience Required: Not explicitly mentioned in the JD.
Versatile technical data scientist capable of translating complex business and scientific requirements into practical, intuitive analytics applications.
Experienced in supply chain analytics with a solid understanding of supply chain management principles and applying data science or decision-support tools in this domain.
Comfortable working in a product-oriented, Agile environment collaborating across technology, business, UX, and data teams with an emphasis on scalable, maintainable solutions.