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Lessons Learned from Applying Data Science in Finance and a Deep Dive into Drift with Mabu Manaileng and Adam Lieberman
Manage episode 424072151 series 2632853
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In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI and ML innovations. First, we have Mabu Manaileng, Lead Data Scientist at Standard Bank Group. Mabu shares his journey and current role, highlights the challenges of applied data science in the financial sector, and discusses the transformative impact of AI on banking in the coming years. Next, we welcome Adam Lieberman, Head of AI and ML at Finastra. Adam defines the concept of drift, discusses statistical measures to quantify it, and provides strategies for maintaining model health, ensuring that models continue to serve users' needs effectively.
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Manage episode 424072151 series 2632853
Content provided by Data Science Salon and Dat Science Salon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Data Science Salon and Dat Science Salon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI and ML innovations. First, we have Mabu Manaileng, Lead Data Scientist at Standard Bank Group. Mabu shares his journey and current role, highlights the challenges of applied data science in the financial sector, and discusses the transformative impact of AI on banking in the coming years. Next, we welcome Adam Lieberman, Head of AI and ML at Finastra. Adam defines the concept of drift, discusses statistical measures to quantify it, and provides strategies for maintaining model health, ensuring that models continue to serve users' needs effectively.
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