The dance between business and technical, concepts and hard data facts. Some concrete examples in which data science was applied to improve business process and improve business models. The art and science behind the use cases, why some POCs (proof of concepts) take flight while others flop.
Key Takeaways
- Some concrete examples in which data science was applied to improve business process, improve business models.
- What are the factors that lead to successful POCs (proof of concepts) to be implemented?
- Why do some projects fail?
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Bio
Goon Yar Jun Caroline – Senior Data Scientist | Manulife | Singapore
Caroline is a pioneer data scientist with almost a decade of work experience in data science and analytics across financial services, commercial and telco verticals. She drives data science initiatives with the business to create value and insights. She identified revenue opportunities and delivered valuable insights across Marketing, Retail & Wholesale Banking, Finance and Insurance. She was also in business analytics roles in JPMorgan and BP.
Caroline received Masters in Applied Statistics and Honours in Engineering from the National University of Singapore, and MBA Essentials from the London School of Economics and Political Science. Her passion is the application of data analytics to drive value creation and to tell the compelling story for the business.
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Goon Yar Jun Caroline – Senior Data Scientist | Manulife | Singapore