What are you learning right now and what cool projects are you currently working on?
Currently I am focused on enabling our customers to harness deeper analytical insights with greater accuracy for improved decision making. Few of the interesting projects that are ongoing right now are — Reject inferencing, prescreen campaigns, recession planning, collection strategies, loss forecasting and peer benchmarking among others. All these projects heavily rely on the power of bigdata, cloud computing, AI/ML.
What is the most significant part of your job?
My primary role is to provide a SECURE enterprise cloud data platform with access to industry’s best-in-class analytical tools such as SAS VIYA, H20.ai, Machinify, PyCharm, R-Studio, Jupyter Note books etc These cutting edge data science tools empowers our clients, some of the top financial institutions in the world, to develop AI and ML models on Experian’s rich data assets.
What attracted you to Experian?
Data is eating the world rapidly with growing digital transformations across the economies. As a result, all the successful companies in various verticals have invested heavily into data strategy. By working for a company like Experian where data is its primary asset, it sets a perfect stage for the technologists that are passionate about solving complex technical problems in the intersection of bigdata, distributed computing, cloud, ML and AI.
What advice do you have for current and future tech professionals?
According to a recent market survey, 2020 estimate calls for 2.7 million job postings for data science and data analytical roles roles. As companies are moving towards a data-driven culture, data literacy has become one of the critical skills for the tech professionals. In addition, I would strongly advice the current and future technologists to develop expertise in cloud computing, Data Analytics, AI and ML Foundations.
