How to improve your work by applying the principles of design thinking

Interview with Victoria Gamerman

What’s in it for statisticians and data scientists?

Design thinking is an interesting topic and is becoming more popular these days. I found out about it on LinkedIn and it’s where I met Victoria.

In this episode, Victoria and I talk about the following points:

  • What is design thinking?
  • Why is it important?
  • What are the different aspects of design thinking?
  • What are the examples for application of design thinking within data science and statistics?


Design Thinking Comes of Age

Vitoria Gamerman, PhD

Head of US Health Informatics & Analytics at Boehringer Ingelheim

As a key opinion leader for real world evidence within the healthcare industry, she has a track record for connecting the dots between meeting patient needs, available data sources, and data science methods.

In her current role, she is the Head of the US Health Informatics and Analytics team, where she enjoys developing and leading a team of experts to optimize clinical trial development by harnessing multi-dimensional real-world data to help meet patients’ needs through the use of advanced analytics and algorithms.

She has a passion for learning, teaching, and promoting statistics and a Scholar-Professional in Columbia University’s Applied Analytics program. She holds a PhD in Biostatistics from the University of Pennsylvania’s School of Medicine.

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