Career Interests
- Julia for Data science
- AWS Cloud Computing
- Internet of Things (IoT)
- Edge Computing
- DataOps(Agile+Dev-Ops) life cycle for Data analytics
- Business Analytics & Strategy
Experience
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Developed recommendation & prediction models for transaction reduction within the context of employee digital workplace services (IT Helpdesk)
Collated data from disparate data sources and mined for deeper insights & identified opportunites for transaction reduction. Developed and validated use cases, used text mining for helpdesk service ticket categorization & developed recommendation models for next best action
Academic Projects
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The Interview Attendance Problem
The data pertains to the recruitment industry in India for the years 2014-2016 and deals with candidate interview attendance for various clients.There are a set of questions that are asked by a recruiter while scheduling the Interview. The answers to these determine whether expected attendance is yes, no or uncertain.To this approach, we used Interview-Attendance-Problem data to predict the attendance.
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Prediction Of Bike Rental Count
The objective of this Case is to Predict the daily bike rental count based on the environmental and seasonal settings.The goal is to build regression models which will predict the number of bikes used based on the environmental and season behaviour. By predicting the count, it will be easy to accommodate the number of bikes required on a daily basis, and being prepared for peak periods. To this approach, we used Bike-rental-Count data to predict the problem.