George Bezerra, Senior Vice President, Head of Data: Why Data Scientists Make so Much Money
Jun 12, 2024
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George Bezerra, Senior VP, Head of Data, discusses career transition from academia to industry, misconceptions about data roles, rising demand for data scientists, salary expectations, and what hiring managers look for in data hires. The podcast covers the evolution of data science roles, criteria for hiring, and tips for understanding job descriptions in the field.
Transitioning from academia to industry with a master's or PhD can unlock a career in data science.
Understanding the evolving definitions of data science roles and the importance of technical skills like Python and SQL.
Deep dives
Evolution of Background and Career Path
George Bazza's career journey from academia in Brazil to transitioning into the industry and his roles at TripAdvisor and The Knot Worldwide showcase the evolution of data science over the years, highlighting the shift towards more technical and diverse skill sets required for leadership positions in the field.
Changing Landscape of Data Science Roles
The discussion delves into the evolving definitions of data science roles across different companies, illustrating how the title of 'data scientist' has encompassed a wide range of functions, leading to varied interpretations and responsibilities within the industry.
Skills and Career Advice in Data Science
Advice on pursuing a career in data science emphasizes the importance of technical skills like Python and SQL, understanding core principles of experimentation and machine learning modeling, and cultivating business acumen to create impactful and valuable insights that drive innovation in the field.
George Bezerra, Senior Vice President, Head of Data
George explains how he transitioned from academia to industry and why earning a master's or PhD can help you unlock a career in data science or machine learning.
We also get George to explain the difference between analytics, data science, machine learning and AI roles and why even companies and hiring managers get it wrong so often. He also shares why everyone suddenly wants to become a data scientist and how much analysts and data scientists can expect to earn. Finally, we get him to reveal what heads of data actually look for when hiring.
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