I have worked on analytics projects where I built a few Machine Learning models, such as a food/non-food classification model, to filter food items from the data pipeline and map them to the appropriate food groups in the AUSNUT database to get their nutrient composition.

This was part of a Benchmarking Project in Australia, where we used sales data, survey data and policy actions from remote Indigenous stores to design policies and actions that could help them develop better strategies to increase the sale of healthy food products and reduce the intake of packaged and ultra-processed products containing high amounts of sugar and salt, with the aim of protecting Indigenous and Aboriginal communities in Australia.

I also worked on a subjectivity analytics platform where we leveraged Twitter data related to food waste discussions to better understand people's emotions and sentiments around food wastage, and how these insights could be used to inform better policy design.

I am currently exploring my Data Science and Machine Learning Engineering skills by working on an end-to-end Data Science project involving demand forecasting for retail stores. Through this project, I want to build my expertise in data analysis, Data Science model building, engineering around the model, and then following MLOps principles to deploy the model on a platform/cloud environment.

I want to keep learning and exploring skills in the Data Science and AI space. I want to use my technical skills to solve real, complex and challenging problems that can benefit society. I may not be an expert in everything, but I would like to build technical depth as well as problem-solving skills and learn how to scope and approach projects, while working towards a noble cause.

I believe this platform will not only help me build these skills but also give me an opportunity to use them to contribute to society.