“I always wanted to mentor different domain people. At Brillio, I had the opportunity to mentor senior and junior data scientists and even data engineering people who needed a deeper understanding of data science. Here, I learned a lot about conciliating people, coordinating teams, and solving internal conflicts to get the work done. Ultimately, we have to deliver the best results for our customers.”
I started my journey at Brillio as a Data Science Leader in April 2021. I chose Brillio because it's a rapidly growing company that provides employees with several opportunities for learning and development and for gaining invaluable experience within a multinational team.
In data science, you can do a lot of innovation. I like Brillio’s culture because there is no stop or limit to whatever innovation I want to do. My manager or leaders never stopped me from exploring anything. I have already been working on building multiple capabilities for Brillio, such as different Machine Learning Solutions for Supply Chain Management, Retail Verticals, and Conversational AI.
My prior knowledge and experience helped me deliver great results with our Center of Excellence. Now, my key focus is to create different Machine Learning solutions/capabilities for the Data Science CoE, as we aim to quickly deliver working solutions to support the customers' plans and strategies.
Soon after I joined Brillio, I started creating different use cases for GDP – Google Cloud Platform, promoting it as an alternative to the AWS or Azure environments. I started pitching different customers, explaining the differences between cloud solutions providers, the cost-effectiveness, and how data science platforms could perform even better and started winning new projects. This is one of my biggest achievements, especially since I managed this only two months after joining Brillio.
This year, my aim is to develop multiple capabilities in retail and supply chain management, which, especially post-Covid, is a very important factor that impacted many businesses. So far, by leveraging data science and machine learning, I have developed six dynamic solutions for supply chain management that we already use for different customers.
I also worked on building a conversational AI for the HR and IT teams. For example, when you want to know how many vacation days you have left, you need to go to different platforms and perform multiple actions to get that data. This chatbot is going to help with that, providing everything with a single click and in one place.
The main challenge with a data science team is in the research stage. It’s difficult to explain to a client that a particular model will take three-four weeks. For data engineering teams, it's easier because they can accurately approximate how much time it would take to deliver. We don't have a mathematical number. We have to explain the logic of why it'll take so much time. To tackle this challenge, I started creating different analyses and designing documents, and every 2-3 days, sending out the decks and sharing them with the other teams and stakeholders. That way, we managed to convince stakeholders that whatever timeline we gave was justifiable.
We have created transparency by de-structuring the project and sharing at every stage. I learned a lot from that project, and now I follow the same approach for every endeavor.
The combination of learning, on-the-job training, and the opportunity to work on many different critical projects with diverse groups of people has greatly helped me with my professional growth. The opportunity to get involved with complex projects and work with the technology you desire, along with the support of the team and managers make Brillio an organization where you can build a long-term career.
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