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Sales Data

Jersey City, NJ
78000 (negotiable)
March 20, 2018

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Pranav Gupta

Jersey City, NJ *****, 201-***-****, SUMMARY Business school graduate with strong quantitative, high statistical modeling and data analysis skills, and a passion for Business Intelligence & Data Analytics. Insight-driven reporting and presentation skills, combined with exceptional multitasking, interpersonal and problem-solving capabilities. EXPERIENCE Data Analyst (Employee Attrition analysis at L’Oréal) Oct 2017 – Dec 2017 L’Oréal collaborating with Stevens Institute of Technology, Hoboken, NJ

• Performed exploratory data analysis, generating and testing hypotheses to find trends and correlation.

• Implemented Tableau for univariate & bivariate data analysis to perform data wrangling operations and feature engineering to identify, measure and recommend improvement strategies for KPIs.

• Built an ensemble of Machine Learning Models using knn, CART and Random Forests for determining the important factors, confidence score and probability of employees to stay in the firm. Business Analyst Intern Jun 2017 – Aug 2017

T.I.M. CORP OF NJ (e-Commerce retailer), Cherry Hill, NJ

• Designed prototype and provided solution for automated synchronization of the inventory with Amazon & eBay to update stock and generate an invoice for each transaction from QuickBooks.

• Provided Fraud Detection solution to verify the customers using their shipping address and social profiles integrated with the above system.

• Performed analysis of the sales data after migrating the data to Azure cloud using SSAS.

• Mitigated the waste flow by statistical analysis of the inventory to liquidate slow-selling products and realizing out of stock products thereby decreasing estimated loss by about $290,000. ACADEMIC


Improving the Marketing Strategy of Taboonette (Manhattan-based food-joint)

• Performed conjoint analysis to assess the importance of attributes and performed cluster analysis of important attributes with the price to recommend improvements for an increased customer base.

• Furnished valuable insights to find potential customers, increased user engagement on social media platforms and digital marketing initiatives.

Predicting Rating of restaurants using Natural Language Processing on Yelp

• Performed web scraping on Yelp website to extract ratings and reviews from customers.

• Extracted the clean text by removing the stop words and performed prediction of text to ratings.

• Implemented Multinomial Naïve Bayes and Random Forests algorithms by pipeline to predict the rating and increased the accuracy score to 93.2% by forging bins. Predictive Analysis of FBI Crime Reports

• Collected and integrated knowledge of FBI crime reports across every city in the United States for dissecting the full range of analytics by performing exploratory data analysis and prompted dashboards to assay the variance over time on Tableau.

• Stimulated regression to fix the null values and transform the data to steer accurate predictions by executing multivariate analysis on SAS.

EVE Online Custom Dictionary

• Performed an exploratory analysis on the forum by deploying LIWC dataset using Tableau by performing univariate and bivariate descriptive statistics.

• Formulated scripts using R to ensure proper data access, manipulation and finding strongly correlated words to create the dictionary and visualized on the period by storyboarding. EDUCATION Master of Science in Information Systems December 2017 Stevens Institute of Technology, Hoboken, NJ GPA:3.9 Courses: Data Warehousing & Business Intelligence, Project Management Fundamentals, Process Innovation & Management, Knowledge Discovery & Data Mining, Supply Chain Analytics, Marketing Analytics.

Bachelor of Technology in Computer Science July 2015 Rajasthan Technical University, Kota, Rajasthan, India GPA:3.3 SKILLS

Programming Languages: C, R, Python, SAS, SQL, VBA Macros Tools: Tableau, MS Excel, MS Visio, SSAS, SSIS, SSRS, Power BI, Agile Methodology, Signavio Certifications: Google Analytics, Statistical Thinking & Machine Learning for Data Analytics

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