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A Day in the Life of a Data Scientist at Pfizer

Use Cases & Projects, Dataiku Product, Scaling AI Catie Grasso

Impactful data science at Pfizer depends largely on having access to the right data, tools, and a network of subject matter experts who can help turn a business problem or scientific question into actionable analytical insights. In this talk (originally held for students and faculty at Stevens Institute of Technology, a Dataiku Academics partner), Neil Patel, interactive analytics and data visualization team lead at Pfizer, and Kristina Cheng, data scientist on the AI insights team at Pfizer, will discuss a day in the life of a data scientist at Pfizer, focusing on the end-to-end analytics process and the various ways in which collaboration occurs at every step.

→ Download: The Next Steps to an AI-Powered Pharmaceutical Industry

Check out the full video below to discover:

  • Pfizer's journey to building data science capabilities to deliver business value, touching on data science talent, tools and technology (including Dataiku), and domain expertise
  • Ways data science can transform healthcare and pharmaceutical delivery (i.e., timelier detection and treatment, interaction data mining from doctor and patient engagement)
  • How Pfizer uses collaboration as part of the data science process, including their iterative framework across people, processes, and technology
  • Real-world examples of how data scientists understand a problem at hand and define the scope of the project (i.e., when to take a predictive or descriptive analytics approach)
  • How the team uses Dataiku as part of its analytics workbench to collaborate on data projects across user types (fast forward to 26:15 for this!)

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