Sales Data Analyst

SHOBHIT SINGHAL

********@***.*** *** W Madison St., Chicago, IL-6066 http://www.linkedin.com/in/shobhit-singhal Summary of Qualifications

Recent Graduate with 3 years of Professional Experience in Data Analytics, Business Intelligence, Database Warehousing, Advance Statistics and Data Visualizations with Expert proficiency in Python, R, SQL, Tableau, PowerBI, VBA and Advance Excel(Macros) Professional Experience

Data Analyst (Assistant Manager), Hero Moto Corp Ltd., India July’13- July’15

• Extracted the sales data using SQL and Performed Exploratory Data Analysis and data Wrangling to predict the buying capacity

• Created Teradata SQL scripts using OLAP functions like Rank to improve the query performance while pulling data from large tables

• Wrote a python based SQL generator that helped speed up a weekly automatic reporting from several days to few hours

• Developed algorithms for optimal set of Stock Keeping units to put in stores that maximized stores sales; advised retailer to gauge Demand transfer due to SKU deletion/addition to its assortment

• Developed Multiple regression models using R studio for material cost reduction (Quote price difference) at various vendors

• Created programs in python for automating the process for creating Excel sheet reading data from Redshift databases

• Tuned SQL Queries by applying indexes and keys; enhanced database performance and lowered execution time by 25%

• Created multiple custom SQL queries in Teradata SQL Workbench to prepare the right data sets for Tableau dashboards

• Created reports with SSRS to generate different reports such as tabular, matrix, drill down and charts reports Data Analyst, Banaao Ltd., India July’15-July’16

• Conducted 10+ churn analysis to improve customer retention and built queries, tables and macros to create 25+ reports Quarterly

• Conducted K-mean clustering using Python for Customer Segmentation based on purchased behavior to better target customer for market promotions resulted in increased of sales by 23%

• Managed reports tracking customers KPI- analyzed the trend across different KPIs and able to translate findings Computational Research Aide, Data Mining and informatics Lab, Arizona State University June’17-Sep’17

• Automated cleaning and processing of 150 + data sources using Python and SQL

• Developed complex SQL stored procedures to aggregate multiple data sources to visualize

• Automated the process of Web Scrapping using Python Script and collected data into central repository

• Rectified the dataset by bagging and boosting technique and resolved class imbalance form Academic/Consulting Projects

Analysis on Credit Risk Modelling (R, Python, Tableau, SPSS) Spring’17 Preprocess and transformation of more than 5 M data by tidyverse. Conducted an EDA, performed Feature Extraction and model the data using Gradient Boosting, Multilinear-Regression, SVM & Random Forest Tools - Tableau, Correlation Matrix, Heat Map, MYSQL Designed the database system and User Interface for Efficient Airline Performance (T-SQL, SQL Server, VBA, Excel) Spring’17 Developed notifications for customers against Cancelled and Diverted Landing factors using relational database and SQL Query Designed the GUI using VBA(Macros)environment; generate the reports of Airlines bad routes using XML and DTD Zappos Customer Segmentation in Retail using RFM Metrics (Python, PowerBI) Spring’18 Computed Recency score of unique invoices and analyzed customer profile using lift and decile Analysis. Outcome: Company can decide whom they should offer discount to maximize high value customers. Tools: K mean Clustering, Random Forest, Time Series Walmart Retail Store Sales Forecasting (Python, SQL, Tableau) Fall’17 Projected the sales for each department in each store and predicted the departments sales affected from holiday markdown events. Used SAS for data prep and statistical methods ARIMA and UCM and used weighted average and trimmed mean of models Model the Pricing Strategy of an Airline Company (Python, SQL, Tableau) Spring’18 Built the predictive model like SVM, Random forest, Neural Networks to suggest a user whether the prices of a particular flight are expected to rise or Fall in future. Tools used: Python, Tableau, Statistical Methods and Machine Learning Technical Skills

Programming languages: R (2 yr Python (Numpy, pandas, Matplotlib, Sklearn, Seaborn) (2 yr Mat lab (1 yr.+) Statistical software: SQL (3yr+), SAP (ERP), VBA(Macros), SPSS (2 yr. +),JMP, Minitab, Weka Relational Database: MYSQL (2 yr SQL Server (1 yr PostgreSQL (1 yr Oracle (1 yr MS Access, Microsoft Azure Data Visualization- Tableau (2 yr. +), PowerBI (1 yr. +), SSRS (1 yr. +), Excel(Dashboards) Education

Master of Science in Industrial Engineering: Specialization Data Analytics and Statistics May’18 Arizona State University, Tempe, G.P.A 3.44/4.0

Bachelor of Engineering in Manufacturing Processes & Automation June’13 Netaji Subhas Institute of Technology, India, G.P.A 3.8/4.0

Contact this candidate