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Me, Myself, and AI

From Data to Wisdom: Novo Nordisk’s Tonia Sideri

27 min • 13 september 2022

Tonia Sideri was a data scientist herself before taking on her role as head of Novo Nordisk’s AI and Analytics Center of Excellence. Now she’s putting her experience to use helping the Danish pharmaceutical company in its quest to develop medicines and delivery systems to treat diabetes and other chronic diseases, such as hemophilia, obesity, and growth disorders.

In a highly regulated industry where failures are costly, Tonia’s philosophy is to fail fast through what she calls “data-to-wisdom sprints.” These two-week hackathons enable her group to rapidly test the feasibility of new product ideas with input from their colleagues on the business side.

Tonia joins this episode to discuss her team’s approach to hypothesis testing, the benefits of incorporating design thinking into building data and AI products, and why she believes empathy is the most important skill a data scientist can have.

Read the episode transcript here.

Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.

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Guest bio:

Tonia Sideri is head of the AI and Analytics Center of Excellence (CoE) at Novo Nordisk, a global pharma company based in Denmark that develops diabetes care products, as well as solutions that target other chronic diseases, such as obesity, growth disorders, and hemophilia.

The CoE is a group of data scientists, machine learning engineers, and software developers located within Novo Nordisk’s Global IT group who work cross-functionally with the company’s machine learning/analytics systems and its machine learning operations platform.

Sideri was a data scientist before taking on a management role. She has years of experience in startup incubators and corporate transformation labs, where she helped unlock the potential of data across the banking, pharma, and biotechnology industries and across a variety of business models, including B2C, B2B, and digital native vertical brands.

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