6 Lessons From Squid Game & How to Apply Them to Data Projects | July 20

Described as "a violent test of morality and humanity", the premise of hit South Korean Netflix series Squid Game, which generated almost US$900 million in value for the company, revolves around debt-ridden players enlisted to compete in a series of 6 childhood games.

While there may not be any obvious linkages between the gory scenes and managing data projects, the TV series does offer deeper points of reflections around both the soft and hard skills that can be used to drive successful outcomes in your data projects.

Join us to hear our creative takes on 6 practical lessons we can pick up from each of the 6 games depicted in the immensely popular drama and how they can be applied to overcome challenges in your next data project.

Download Zoom. Zoom is the video conferencing tool we will use. It works a lot like Google Hangouts or Skype.

Kishan is a seasoned data and marketing professional with a proven track record across all key areas of digital including Data Mining, Data Science, Data Visualisation, Data-Driven Transformation, Sentiment Analysis, Data Storytelling, Web Analytics, Social Analytics, App Analytics, Advanced Analytics, Omni-channel Tracking, Paid Social, SEO, SEM, CRM, E-Commerce, and Digital Strategy

He has worked for 4 of the world's leading digital technology agencies: Amobee, Golin, Datalicious, and Socialbakers. Throughout his career, he has managed hundreds of digital campaigns and built several digital teams from ground-up, working with a diverse portfolio of local and global companies – including some of the world’s biggest brands: McDonalds, Sony, Prudential, Volkswagen, and Cartier.

Kishan also has extensive hands-on experience in Data Science where he has worked with E-Commerce and FMCG clients to build Machine Learning models to enhance the performance of product recommendation engines and drive profitability of product bundles among other areas.

He has also previously worked as a data scientist, automating data extraction from Weibo and Taobao to measure the impact of online retailers' social media marketing strategies on consumer engagement and sales performance using quantitative methods including random-effects panel regression.

Throughout the past decade, Kishan has also worked on other interesting Data Science projects including a predictive modelling app which allows users to find the number of parking lots at their destination for a given location and time slot. He also built an innovative sentiment analysis model for a software company to evaluate their customer satisfaction rate using data extracted and automated from customer support tickets.

Kishan's experience has also centred around managing business growth and day-day operations for data-driven marketing start-ups in Asia. Having built and led several high-performance digital teams and programs in the past decade, Kishan combines management experience with deep subject matter expertise across business analytics, data science and digital marketing. He is also highly skilled in leveraging MarTech to grow digital revenue and reduce customer churn for leading brands in Asia including Singtel and Globe Telecom.