Episode 93: [Value Boost] What Industry Data Scientists Can Learn from Academic Training

About this episode

This episode explores the valuable skills that academic-trained data scientists bring to industry and how these strengths can be developed by all data scientists.

While the transition from academia to industry can be brutal for data scientists, academics don't show up in industry empty-handed. They bring powerful transferable skills that many industry-trained data scientists never develop. In this Value Boost episode, Dr. Sayli Javadekar joins Dr. Genevieve Hayes to flip the script on their previous conversation, exploring the valuable skills that academic-trained data scientists bring to industry and how any data scientist can develop these same strengths. You'll learn: The most valuable skills academics bring to industry [01:30] Why the experimental mindset matters so much [03:43] The hidden benefit of extended research projects [04:54] How mentorship can work both ways for mutual benefit [07:06] Guest Bio Dr Sayli Javadekar is a data scientist at Thoughtworks, with experience at the World Bank and UNAIDS. Before this, she was an Assistant Professor at the University of Bath and holds a PhD in Econometrics from the University of Geneva. Links Connect with Sayli on LinkedIn Connect with Genevieve on LinkedIn Be among the first to hear about the release of each new podcast episode by signing up HERE

People in this episode

Host: Dr Genevieve Hayes

Guest: Dr Sayli Javadekar

Topics covered

• data science
• academic training
• industry skills
• transferable skills
• mentorship
• experimental mindset

Keywords

• data scientists
• academic training
• industry transition
• transferable skills
• mentorship
• experimental mindset

Mentioned in this episode

Organizations: Thoughtworks, World Bank, UNAIDS, University of Bath, University of Geneva

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