Parag Saxena

About Parag Saxena

A Data Scientist with several years of experience and skilled in SQL, Python, Data Analytics and ETL. Good team player, capable of leading or working as part of a group. Quick learner & ability to work under pressure on multiple projects simultaneously. Adaptability with excellent communication skills that are vital to work environment. Open to new ideas & always keen on learning. During my career, associated with some of the Big Clients like Microsoft, Intel, AIRBUS, Bank of Singapore and Scholastic Inc. I started my career as an SQL developer where I have Implemented on Extract, Transform, Load (ETL) as Data Engineer. After working as a Data Engineer(ETL Specialist) for more than 6 years. I have upgraded my self by completing online Post Graduate certifications on Cloud computing and Data Science. After that started using AWS cloud for ETL work and at the same time also started implementing Machine Learning Models using SKlearn. As my interest in Data kept growing, I decided to learn Data Science my enrolling into Masters in Data Science a full-time student. During my first project with Microsoft, I created Data Models for migration from OTLP to OLAP using ETL tools like SSIS. My efforts lead to better data quality, which was instrumental in increasing the customer satisfaction index from 3.5 to 4.2 for Xbox support. After working for 1 year in US, I started my new assignment in Singapore with client as Bank of Singapore, As a Data ML Architect, I have worked closely with Product team to improve the prediction capability from 57% of ROC-AUC to 64% of ROC-AUC for high net worth client with their investment of more than 2 million dollars each. I contributed positively to increase the net Revenue of Portfolio Management by 100 Million Singapore Dollars. Later in my Career working with Capgemini, I have directed two Agile teams, one on Data Engineering and the Other on Data Science as Manager of Data and Insights. I was able to create a conducive environment for client integration with efficient delivery of Data pipeline and ML pipeline. My efforts were instrumental in saving 100 hours of non-automated efforts per month in Data pipeline, While in ML pipeline I spearheaded inventory analytics ML model which saved around 20 million dollars by reducing ground zero hours of the Airline. Skilled with Data Science and Data engineering background, I aim to explore multidimensional roles such as Senior or Lead Data Scientist, capitalizing on the skills I acquired in Masters in Data Science Program. Contact: s••••••••@hotmail.com or p•••••••@unnc.edu

Experience

1. Data Scientist

   EPRI

   May 2023 — Present · Charlotte, NC, US

Education

• Indian Institute of Management, Indore

  IPBA, Business Analytics

  2020 — 2021

• Great Learning

  Post Graduate Program in Cloud Computing, Information Technology

  2018 — 2019

• University of North Carolina at Charlotte

  Master's degree, Data Science

  2022 — 2023