Vipin Mathew

Working as part of Big Data and Machine Learning team at Barclays Global Service Center Private Limited. My responsibilities include building models and getting insights from data using R, Python, SQL and Spark. I act as a consultant for teams across Barclays to leverage machine learning to improve efficiency and deliver business value.

• Development and application of machine learning algorithms to detect and prevent credit card frauds. Using pySpark for feature engineering on 1.5 Terabyte of credit card transactions and building fraud detection models using XGBoost and Deep Learning algorithms.
• Working on improving Fraud Detection algorithms used by Barclays Partner Finance, one of the UK's largest providers of point-of-sale finance for retail companies and motor dealerships.
• Implemented strategies for improving customer journeys through IVR system and reducing calls getting dropped to agents in Customer Contact Centers. Worked on big data analysis in R using data.table and tidyverse packages.

• Built a Chatbot on Facebook messenger platform which was released to selected customers as a pilot. Implemented Natural Language Processing models using NLTK, spaCy to understand a user's intent and automatically reply to queries related to Barclays.
• Reduced average time spent in amendment of a client’s account from 18 minutes to 8 minutes and minimized keystroke errors impacting customers by 80%. QA Automation application, part of Project Waterfront, developed using IBM BPM handles the end to end workflow for performing QA for an account.

• Authored a paper titled "Sensor Health Monitoring using simple data driven approaches" which was presented at Indian Control Conference 2016 and published by IEEE.
• Developed fault diagnosis and prognosis techniques for automotive sensors.
• Involved in CREST R&D team which suggested strategies for reducing cost while retaining existing features of Land Rover vehicles.