• Analyzed and reported number of weekly hours saved in Sanity and Load Testing triage by generating weekly reports • Enhanced product quality in concurrent sprints by developing dashboards on Excel and identifying analytic insights • Performed scaled automation using python test framework resulting in 10% increase in defect identification across SKU’s • Developed automated python script for Sanity and Load Testing failure triage process reducing manual efforts by 18% • Devised an end-to-end testing on storage systems project by designing several automation test scripts using selenium • Designed various test cases in accordance with the given business requirements by improvising on previous test cases • Reviewed new areas of opportunity in daily agile standup meetings with team leads, product owner and stakeholders
Projects
Predictive Analytics: Frito-Lay Data Analysis Using Microsoft Excel & SAS • Performed ad hoc data analysis on 9 million records to visualize market share and weekly sales by product categories • Identified key metrics affecting odds of people buying Fritos product by designing multinomial logit model with 83% accuracy • Forecasted overall sales of Fritos brand and drilled down the forecasting on market and product level using ARIMA model • Predicted number of units at market level for various product types to efficiently manage inventory across 140 locations • Utilized demographics coupled with customer segments using Recency Frequency Monetary analysis to get crucial insights
Machine Learning & Predictive Data Analytics: Walmart Sales Prediction Using Python • Analyzed the impact of Markdown values and Holidays on Weekly Sales of various departments for 45 Walmart stores • Forecasted overall sales for 3 months by store type using Auto-ARIMA predictive model with RMSE of 407.8 units • Improved accuracy of sales forecast by implementing GRU predictive model to reduce the root mean square error by 6.14% • Created an ensemble regression model by taking average of regressors to reduce RMSE and improve accuracy to 97.18 %
Big Data Analytics: Exploratory Data Analysis Using Tableau & Hive • Imported geolocation and truck information data into Hadoop File System by incorporating external tables using Hive • Eliminated the skewness in the data by identifying and normalizing risk factor associated with truck accidents • Identified cities prone to high number of accidents by integrating Apache Hadoop with Tableau dashboards
Business Analytics with R: Bitcoin Price Prediction Using ARIMA Forecasting • Utilized cryptocurrency, crude oil and stock price variables to improve forecasting accuracy of bitcoin prices by 9% • Visualized periodogram and analyzed results to identify the trends in bitcoin prices based on seasonality • Optimized ARIMA model to efficiently forecast bitcoin prices and visualized the results using ggplot2
Data Visualization: Integrated Analysis Using R and Tableau • Identified insights and key performance indicators by implementing decision tree and K-means clustering algorithm • Designed interactive and compelling dashboards on Tableau to effectively analyze analytic insights affecting the survival rate