Written on 08 September 2020.
It was a hackathon in partnership with Burger King and Sutter Mills (now, Accenture): Activating a Multinational’s Data to Prevent Churn. They challenged the MSc in Data Analytics & Artificial Intelligence students to make the best use of the data available in order to predict, monitor, and prevent churn.
The project involved 10 teams of 6 to 7 students.
The project was extremely complete. It required both technical skills and business acumen. We were tasked with a churn predictive analysis using AWS Athena and Sagemaker platforms, as well as with a dashboarding analysis to monitor the trends in loyal customers’ churn. Lastly, presentation support, business-oriented, needed to be pitched to Burger King and Sutter Mills (now Accenture) since our team was in the three finalists.
This challenge enabled me to make thorough use of the technical skills I acquired in the MSc in DA & AI combined with the business background from my undergraduate studies in Canada. Not only did it require solid theoretical knowledge of the machine learning algorithms put into place, it also meant mastering two Softwares: Tableau and AWS, as well as being able to code in Python and SQL. However, delivering great technical details are useless without good communication and presentation of results/implications.
The MSC in DA &AI partnership with Burger King/Sutter Mills (Accenture now) gave me the opportunity to apply a year-round of knowledge into a practical study of customer behaviour. Being able to see all our learning applied for the use of a real-life company was incredibly rewarding for our team. The MSc students are also very different background-wise, and it was absolutely great to work with students that had a double master with engineering, some that specialised in dash-boarding and others in data science. We were also coached by the Sutter Mills team (part of Accenture) which lent us great advice, just like seniors may give.
I think this project embodies what I ultimately would be thrilled to work on: practical use cases of data to understand customer behaviour that require both a solid understanding of machine learning, but also the ability to work in a team and share the results with the marketing field.
It has also allowed me to perfect my understanding of AWS and python: two tools crucial in data analysis these days.
As a young graduate specialised in Data Analytics and Data Science, I aspire at the ethical use of data to understand customer behaviour, most specifically in the marketing field. I strongly believe that the techniques we have learned, if properly put into place and with the respect of privacy, can benefit both businesses and individuals.