Behind The Screens: Meet The Woman Who Built Shopee's Data Science Team From Scratch

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#Behind The Screens: Meet The Woman Who Built Shopee's Data Science Team From Scratch

This article is about Dr. Pan Yaozhang, Head of Data Science at Shopee. Shopee has such a large share of the e-commerce market today, and many people think he is the main credit. Launched in Singapore in 2015, Shopee has gone from being a buy-and-sell site to becoming the one-stop-shop for shoppers looking to get a good deal on trustworthy products offered by trusted merchants and is also listed on the New York Stock Exchange (NYSE). Dr. Pan Yu Zhang said that as the head of Shopee's data science decadence, she has three main areas of work. First of all, in terms of team management, it is his responsibility as a supervisor to motivate employees. She helps them quickly understand the working purpose of employees and the impact of Shopee's business strategy. They are also encouraged to use data science to propose more innovative solutions to promote more efficient e-commerce projects. Secondly, to supervise the implementation of the project, Dr. Pan Yu Zhang stated that it does monitor the implementation of the project so that the company's overall operation will not be delayed, and assists in connecting with other departments. Last but not least, as artificial intelligence and data science are booming, it takes time to update the latest new technologies, keep up with the pace of technology, and develop new and responsive technologies for the entire company. Through seminars, report the latest progress to the company and assist other departments to keep up-to-date technical development information. Data analysis is the core of Shopee. It has been using data monitoring and analysis since its inception.Currently, the role of the data science team at Shopee is to use artificial intelligence and data science technology to drive the business, optimize important business processes, and improve key business metrics. By optimizing business processes, time can be reduced, and valuable data can be screened to improve the user experience, thereby reducing costs and improving operational efficiency.

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