According to Vikas the most exciting thing about the work is that it is very fast-paced, and the learning is exponential.

Can you share the most interesting part of your career journey?

I have been associated with Deloitte for more than five years and the data science field for more than 10 years. The most interesting part of my career journey is being able to work with different clients across industries and receive exposure to their ways of working. Being more of a technical person, I love solving complex business problems and thinking about how data science solutions can be implemented, creating an “impact that matters.” The learning curve is steep; there is always something new to learn, whether building business skills or even soft skills or translating business problems into analytical ones. This entire journey has been quite enriching, helping me expand my knowledge. I have been fortunate enough to work on some challenging business problems.

What excites you most about working with data and AI?

The most exciting thing about the work is that it is very fast-paced, and the learning is exponential. I love understanding the client’s pain points and thinking through how data and analytics can be used to solve these business challenges.

The most interesting part is accepting the challenges and finding a solution by interpreting data and reading between the lines with the numbers narrating the story. Working with data provides an opportunity to understand the behaviour and identify what when, whom, and how to predict.

AI has the potential to solve high-level tasks. With the fast growth of AI and new advances being made in this area each year, we are not only improving the speed of doing various tasks but are also able to achieve the impossible, which can make a huge impact on the life of people.

For any line of business, AI and data analysis offer a very broad scope that cannot be limited to any activity.

Describe an interesting project that you have worked on.

One of the interesting and recent projects I have been a part of was working for a South African telecom client. The objective of the project was to identify the customers who were more likely to drop their revenue and churn in advance to minimise the revenue loss by retaining those customers.

This involved analysing the usage and recharge behaviour of the customer and deciding the segments and time in advance to predict the customers. Analysing the KPIs and transforming them for our business use; finding the Machine Learning solution, which could precisely predict the customers; implementing it to run daily, reducing the customer churn and improving overall client revenue were some of the interesting aspects of the project.