I represent the Data and Analytics team and work on everything related to Data Science and AI. As a data science digital advisor my responsibilities are broad. I work extensively on the entire data science life cycle, starting with collecting and understanding client data, deriving insights to deploying up to productionizing Machine Learning models at the end. Being partners with Microsoft, we regularly use Azure ML and other Azure services for both development and deployment. But beyond developing solutions, I also get to help our clients make AI and ML work for their businesses. Many a times businesses want to transform and become data-driven, but they lack a clear roadmap. We guide them and begin with ideation, prioritization of use cases which I enjoy doing, before moving on to implementation.

The day starts with a daily catch-up with the data science team, where we discuss and plan our tasks for the day ahead. I also answer my emails while I’m fresh. A quick look at the schedule later, I begin to prep for any calls and presentations coming my way. This is usually followed by a few of hours project work before breaking for lunch. The afternoons are more meeting heavy seeing that our colleagues and clients are mainly Scandinavia based. A few hours every week are spent learning and trying out new technologies, prep for certifications and working towards Columbus’s goals, e.g., Sustainability: Green Coding? When I work from office, the day is packed with discussions with peers, catch-ups, gaining insights from seniors and a compulsory hour of intense table-tennis