Sign in

Data Marketing

Richardson, Texas, United States
January 27, 2018

Contact this candidate


Phone: (971) ***-****; Email:


Highly motivated data enthusiast with expertise in programming, data analysis, statistical modelling, data visualization, reporting, project organization and analytics. Competency in analysing data, organizing and reporting them to improve efficiency. Good decision driven analytical problem solving capabilities with demonstrated success in various academic projects.

•Experience with large datasets for data preparation, cleaning, wrangling and feature extraction

•Experience writing complex SQL queries for data analysis and reporting

•Experience in predictive modelling, data mining, clustering, forecasting and statistical analysis

•Experience using statistical and machine learning packages in R and Python

•Experience with VLOOKUP, pivot table, formulas, macros, data analysis, solver tools in MS Excel

•Strong understanding and academic experience in data warehousing, business intelligence and data modelling

•Good communication skills - interactive and engaging presentation skills to varied audience


Google Analytics Individual Qualification Certified Google AdWords Fundamentals Certified


Basic: Big Data, Spark, Hadoop (Hive, Pig), STATA, VB, Java, Text Mining, Natural Language Processing (NLP)

Intermediate: Python, R, SAS, Google Analytics, QlikView, Power BI, MS Access, CA Erwin, Google AdWords, ML algorithms

Advanced: SQL, Tableau, MS Excel, PowerPoint, MS Office


M.S., Business Analytics August 2016 – Present

The University of Texas at Dallas GPA 3.2

B.E., Electrical and Electronics Engineering August 2011–May 2015

Anna University, Chennai, India GPA 3.2


Johns Hopkins University – School of Medicine, Baltimore, MD Summer 2017

Programmer Analyst Intern

• Developed an end to end process (Identifying KPIs) to automate existing manual reporting process

• Analysed existing excel reports to identify KPIs for efficient Budget allocation for research space to maximize efficiency

• Reduced manual effort of reporting by writing stored procedures in SSMS and automated the process for yearly basis

• Built interactive dashboard to visualize Budget allocation trend YoY (year) using Tableau

LTI - Larsen & Toubro InfoTech, India Summer 2016

Internship- Machine Learning Techniques to Handle Data Sparsity

•Data cleaning and exploratory analysis of customer data sets in R

•Implemented algorithms for classification to predict customer churn and metrics were derived for business decision making

•Researched on optimization techniques to improve the prediction accuracy of the classifier


Programming for Data Science (Python) – Lahman Baseball data September 2017

•Analysed Baseball Statistics data to compute Batting averages, OBP & other stats of interest using Python Data Analysis libraries

•Developed effective data visualizations using Python libraries (Matplotlib & Seaborn) to identify new patterns and trends for better insights

Marketing Predictive Analytics using SAS Jan 2017 - May 2017

Short-term work project - Domino's Pizza (Predictive Analytics for Domino Pizza Target Mailing)

•Developed a model to identify respondents to a promotion from the nation-wide customer base

•Analysed sales data, hundreds of coupons and promotions and customer buying behaviour in the 15 large market sectors

•Predicted customers for target mailing of promotional offers using A/B testing, K means clustering and Logistic Regression

•Identified which customers were at risk and this enabled the organisation to reach out to these customers and offer incentives

Web Analytics - Google Online Marketing Challenge April 2017 - May 2017

•Designed ad campaigns to improve brand awareness of a start-up company (DING - The Store) to promote sales

•Implemented several bidding strategies to achieve a target of 10000 impressions and analysed traffic through Google Analytics

•Ensured SEO success by evaluating site traffic quality and content engagement

Business Analytics with R - Predicting Bank Telemarketing Success Aug 2016 - Dec 2016

•Identified the right customer target base to maximize annual revenue for the organization

•Performed predictive and descriptive analysis for target marketing of a banking scheme

•Created a BI model that involved exploratory analysis, pre-processing of data, unsupervised and supervised classification techniques

•Determined the most probable customers using machine learning algorithms (Clustering, KNN, Decision Tree, Logistic Regression)

Marketing Management – Sprint Corporation, Inc., Aug 2016 - Dec 2016

•Performed SWOT analysis to get a precise understanding of the company to identify a problem impairing revenue

•Evaluated the 3C’s and 4P’s to understand the marketing environment of the organization

•Developed a detailed marketing plan – STP, marketing mix, long term plan and profitability projection

•Suggested possible organizational improvements to better profits


First Place in Marketing Analytics Challenge, UT Dallas May 2017

Intelligence and Analytics Society – Member August 2016 – Present

Contact this candidate