Sign in

Data Analyst / Data Scientist

Dallas, TX
November 04, 2019

Contact this candidate



Email: Phone: 469-***-****


THE UNIVERSITY OF TEXAS AT DALLAS, DALLAS, TX December 2018 Jindal School of Management

Master of Science in Management Information System Relevant Coursework: Statistics, Predictive Analytics, Data Mining, Python, Exploratory Data Analysis, Big Data THAPAR INSTITUTE OF ENGINEERING AND TECHNOLOGY, PUNJAB, INDIA May 2015 Bachelor of Engineering, Electronics and Communication Engineering SKILLS

Database : SQL (MS SQL, Oracle), POSTGRESQL, Entity Relationship Diagram, Microsoft Visio

Languages: Python (SciPy, Numpy, Pandas, Scikit-Learn), RStudio (dplyr, ggplot, gbm, mice, caret)

Digital Marketing Tools : Google AdWords, Google Analytics, Adobe Analytics, Omniture Analytics

Big Data Tools: Hadoop, Hive, Sqoop, Pig, Spark, Mahout, AWS

Visualizations : Tableau, R-Shiny, Microsoft Excel (VLookup, HLookup, Pivot Table), QlikView

Machine Learning Algorithms : Regression, Classification, Clustering, Regularizations, Time Series Analysis

Statistics : Hypothesis Testing, Bagging and Boosting, P-value, T-Statistic, Cross Validation, Sampling Techniques EXPERIENCE

Kellton Tech (Chicago, IL) – Data Analyst January 2018 – February 2019

Created a classification model in Python to predict customer churn using Logistic Regression, Decision Tree, Random Forest. Used this model to recommended better marketing and service strategies to reduce the churn rate by 5%

Conducted A/B test to explore if certain marketing patterns had significant effect on improving sales performance

Developed Tableau Dashboards and reports using crosstabs, heat maps, geographic maps, pie charts which depicted performance across sales, marketing and technology ACADEMIC PROJECTS August 2016 - December 2018

Ridership Prediction (Tools : Python): Developed a predictive model to forecast daily ridership for Adventure Landing Dallas (Amusement Park) using Random Forest; Achieved 12% cost savings and reduction of 27% in error over the baseline model engineered by the park

Claim Fraud Detection(Tools : Python): Built Decision Trees, Ensemble models, logistic regression to classify fraud claims based on historic claim data; Tuned model parameters by determining cut off value based on sensitivity and precision values improving performance (F-score by 4%)

Web Analytics (Tools : Google Analytics, Google Adwords): Increased website traffic using Google Analytics for an e- commerce start-up “The Veshti Company” by 37%; Performed Clustering Analysis to find out performing keywords leading to decrease in CPT; Designed custom SE optimized ads using Google Adwords to increase CTR, decrease avg CPC by 13% and increase conversions by 9%

Database Modelling (Tools : SQL): Redesigned existing database to handle the increase in data volume and transactions; Optimized the database to handle videos, images and text thereby enhancing the hospital’s patient records; Inculcated the database with the ability to generate reports to track pharmacy stock and ambulance availability

Sports Analytics (Tools : Python): Applied Association rule mining to uncover player attributes impacting success of a soccer team


Activities and Societies: IAS (Intelligence and Analytics Society), MIS (Management Information Systems Club)

Certifications: Google Analytics, Google AdWords, Python for Data Science (DATACAMP)

Contact this candidate