I am a Research Assistant at the University at Buffalo, where I am examining deep learning and traditional methods for simultaneous localization and mapping (SLAM) in various space environments. This is part of my Master’s in Engineering Science program, which I am pursuing to advance my expertise in data science and solve intricate real-world problems using data.

Previously, I was a Data Science Manager at Philips, where I spearheaded the development and democratization of a scalable engine for marketing analytics, capable of market mix modelling, forecasting, promo evaluation, and report generation. I also automated data pipelines in collaboration with data engineers, integrating data from multiple sources such as online and offline retailers, media platforms, and brand influencers. I have six years of experience in designing and implementing data science solutions and products for diverse industries and domains, such as medical devices, consumer banking, architecture, and mining. I have a proven track record of delivering value to clients and stakeholders by harnessing the power of data, machine learning, and first principles thinking.

As an active participant in Kaggle competitions, I have attained the Expert level and consistently ranked among the top 2% of the Kaggle community with a best of 0.3%. My passion lies in exploring cutting-edge technology, leveraging my extensive industry experience and academic pursuits, and applying it to make a positive impact on customers and society.