I have 15 years of experience in the IT industry and have played multiple roles across projects . I have been in the Data Science domain for the past 3 years and have worked on several projects across domains like Telecom and Retail. I like the challenge of a Data Science project and want to continue working in the same field . My resume will highlight only the projects associated with this stream thereby not putting much focus on my previous work experience.
The goal is to predict whether a package would be delayed, If delayed then by how many days and all this has to be done at the earliest stage of the order journey especially before order dispatch .This pilot is for a major European Retailer who is looking to reduce the penalty for delayed shipments.
It involved identifying pain points like lead time issues, defaulting delivery partners and problematic regions and finally predicting the delay for each shipment.
The requirement was to identify the pain points of a 5G RAN network build process of a major American Telecom Service Provider and subsequently optimize the build duration and the associated business process . It included writing queries to extract data from the source database, cleaning and transforming the data, performing EDA and modelling to estimate milestone and project duration .
I worked on classifying API failures for a mobile SIM card related business process for a major Indian Service Provider . The process called for identifying failure rates for APIs involved in backend transactions and predicting when such failures would occur in the future. This also helped the business to understand what APIs are prone to failures during what time periods
The goal was to predict whether a particular milestone in the network build process of a major Telecom Service Provider would be delayed from the agreed date thereby inviting penalty .
The customer was a major American marketing company that needed to understand what customers would be likely to click on their ads and subscribe to their offerings and what are the factors that influence their decisions
The goal was to optimise the business process for a major European Service Provider by modelling their milestone durations and identifying data integrity, data quality issues
Machine Learning
Large Language Models application through production
Large Language Models application through production
PGD in ML & AI