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Data Analyst Marketing

San Francisco, CA
August 01, 2020

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GitHub 214-***-****

San Francisco,CA


The University of Texas- Dallas May 2020

Master of Science in Business Analytics GPA: 3.44

University of Mumbai June 2015

Bachelor of Engineering in Electronics Engineering GPA: 3.6 SKILLS:

Programming Languages : R(ggplot, dplyr, shiny), Python(Pandas, numpy, Scikit-Learn),SQL Business Intelligence Tools : Tableau, Excel, SAP Business Object Statistical & Machine Learning : Regression, Clustering, Tree Based Methods, Hypothesis Testing,Time Series WORK EXPERIENCE:

Senior Data Analyst July 2020 – Present

R Square Analytics, Atlanta GA

• Analyze both customer transactions and competitor datasets to provide insights and strategic recommendations on how the brands can increase sales, gain market share, promotion, pricing efforts, and identify strengths, risks, & opportunities for the brands.

• Implement Demand forecasting models for products that leverage consumer insights, client-planned marketing inputs, and relevant in-market data in CPG domain. Data Analyst Jan 2017- Jul 2018


• Analyzed consumer response across channels and brands and quantify the overall impact of multi-channel initiatives.

• Designed dashboards and automated month-end analysis of business performance metrics for a leading Australian Bank using Xtraction tool and complex SQL queries resulting in 20% increased efficiency.

• Extracted, interpreted and analyzed consumer behavior data to identify key metrics and transform raw data into meaningful, actionable insights using Tableau that generated $50K in additional revenue. Junior Data Analyst Dec 2015 – Dec 2016


• Analyzed detailed customer profiles along with transaction data to improve acquisition, retention and revenue through cross and upselling initiatives for a leading US Bank.

• Evaluated KPIs to extract actionable insights and suggest recommendations to evaluate the success of business initiatives through performance reports created via SAP BO

• Build and improve weekly& monthly reporting that help the stakeholders understand the performance of their business segment and identify action points


• Peanut Butter Brand Marketing Analysis SAS

Analyzed large datasets, articulated product questions, used statistics and performed competitive brand analysis to provide insights on factors that influence the sales of a brand across 700 stores in SAS

• Bank Marketing Analytics Pyspark

Analyzed direct marketing campaign data for a Portuguese Banking institution and predicted if the customer would subscribe to a term deposit or not using MLlib.

• 50 Years of Pop Music Lyrics R

Analyzed music data and performed sentiment analysis to identify trends in music lyrics and visualized in Shiny App

• Credit Card Fraud Detection Python

Analyzed over 200K transactions made by credit cards to detect fraudulent activity. Achieved 92% Precision-Recall Score in detecting fraudulent transactions using Random Under-Sampling Techniques and Random Forest Classifiers on PCA transformed variables . Logistic/Linear Regression, GLM, Decision Trees Random Forest, GBM, xgBoost Redshift, BigQuery, Snowflake PCA SVM,, linear and logistic regressions

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