drawing

Click here for my Linkedin profile

Sreeparna Chatterjee

Hello everyone, I am pursuing my Master’s in Business Analytics from the University of Cincinnati. I bring with me, a Master’s in Statistics and over 4 years of experience working as a business analyst for India’s largest e-commerce platform Flipkart. I have worked for the Supply Chain leg of Flipkart driving business with highly scalable and impactful solutions through robust data driven solutions.

Academic Background

Professional Background

I have over 4 years of experience working as a business analyst for India’s largest e-commerce platform Flipkart. I have worked for the Supply Chain leg of Flipkart driving business with highly scalable and impactful solutions. I am keenly interested in exploring the scope of data science and advanced analytics, and diversifying it beyond computational fields especially in the Operations field of Logistics and Supply Chain.

I have 4 years of technical experience with a rigorous exposure to coding in Python, R, and SQL; and dashboarding in Power BI.

Experience with R

I have worked in R for almost 5 years now right from my Master’s. Major Projects in R:
● Exploratory Data Analysis: I have created multiple EDA frameworks for comprehensive data analysis to identify data patterns, outliers, basic summary, distributions, treat missing values and create a clean analytical data set that can be used for modelling

● Modelling: Multiple Regression and Random Forest Projects- Increased last-mile conversion from 82% to 89% in a single quarter and decreasing supply chain cost by drivers identification of the last mile conversion and customer availability using Random Forest and Multiple Linear Regression, Identified attrition drivers of logistic partners using random forest and logistic-regression- reduced attrition from 23% to 15% between Dec ’19 to June ‘20

● Clustering: Extracted customer hotspots across cities using OPTICS clustering to scale up new delivery models like “Kiranas”(small stores partnering with Flipkart for last-mile delivery) and “Lockers”- onboarding 10000 new “Kiranas” using the model suggestions between Jan-June ‘20

● Text Analytics and Sentiment Analysis: Understanding customer pain points by text mining-Topic Modelling customer text comments with the last mile delivery using LDA and Sentiment Analysis. Determined how to handle deliveries with COVID protocols and improve customer sentiment

Most frequently used libraries: ● tidyverse ● dplyr ● ggplot2 ● stringr ● topicmodels ● tidytext ● reshape2 ● glue ● SnowballC

Technical Skills

  • Excel
  • SQL
  • R
  • Power BI
  • Python
  • Tableau
  • Hive
  • Azure