#39 - 2021.10 - Applying DS in the debt collection

🆂🅻🅾🆃 #0: 18:00-18:10 - Welcome

🆂🅻🅾🆃 #1: - 18:10-18:55 - Challenges and learnings in applying DS in the debt collection business - Igor Smirnov

As a data scientist, I am very interested in how real business applies analytics and machine learning and benefits from it. Generating business value from data is one of my favorite challenges, and I want to share my experience with you. The potential of data science in debt collection has not been explored thoroughly. Hence, there is huge room for establishing the best practices in machine learning and data engineering.
During this talk, I will guide you through the main stages of a data-related project. Starting from an initiation phase where business struggles with a particular problem. Up to an implementation phase where a cross-functional team can deliver direct value to the company.
In addition, I will touch on some important challenges, like data quality and security, validation of results, and collaboration among different teams. This talk will encourage you to use an analytical approach in the financial domain by showing a comprehensive picture of a data science project.

👨🏻‍🔬 Igor is a data science consultant at Crayon Austria, focusing on retail, banking & finance and predictive maintenance analytics, as well as data infrastructure. He is a member of an educational open-source project X-Technology and occasionally blogs about data on Medium.

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