Data Analyst

ROHITH YEDOTI

Mail Id: *****.******.*@*****.*** *220 McCallum Blvd, Apt 1203, Dallas, TX

Phone No: +1-682-***-**** https://www.linkedin.com/in/rohith-yedoti- About Me:

A data enthusiast with good knowledge of Analytics tools and techniques who is passionate about using data to create realistic insights and identifying actionable business opportunities through extensive statistical analysis and information research. EDUCATION

The University of Texas at Dallas Dec 2017

MS in Business Analytics GPA 3.84

National Institute of Technology Calicut May 2015

B.Tech., in Electrical & Electronics Engineering

TECHNICAL SKILLS & CERTIFICATIONS

Certifications: SAS Base certified programmer, R programming, Python for Data Science.

Programming: SQL, R, SAS, Python, VBA

Software: Tableau, MS Excel, Power BI, QlikView, MS Office Big Data: Hadoop, Hive, Pig

Databases: Oracle, DB 2, SQL server, MySQL

Datamining: Text Mining, Decision Trees, Market Basket Analysis, Clustering, PCA, Random Forests, Neural Networks, Support Vector Machines, Recommender Systems, Boosting, Bagging, Bayesian Networks, Time Series Analysis, Conjoint Analysis. Statistical Techniques: Logistic, Multiple Regression, ANOVA, Hypothesis Testing, Factor Analysis

WORK EXPERIENCE

Achievement First, New York June 2017 – August 2017 Data Analyst Intern

• Worked as a Data Analyst Intern with a team of Data Analysts to produce the highly anticipated annual network- wide state-test analysis.

• Cleaned the collected data and processed assessment data received in raw form from state education departments and the College Board to fuel the team’s summer analysis and reporting projects. [Used: SAS, R, Tableau, SQL, Excel]

• Conducted key quality control processes to ensure that team output is 100% accurate.

ACADEMIC PROJECTS

Database Foundations August 2016- December 2016

• Implemented SQL queries using joins and nested queries on more than 15 tables to retrieve data from database.

• Designed ER diagrams to analyze logical and relational database for a furniture company.

Predictive Marketing Analytics January 2017 - April 2017

• Implemented RFM Analysis in SAS and analyzed the demographics of high value customers by segmentation.

• Conducted time series for forecasting sales on weekly, monthly level to manage inventory and logistics of a store. Business Intelligence Software and Techniques

Predicting Profitable Donors August 2016- December 2016

• Predicted the most profitable donors for a charitable organization based on their previous postcard mail solicitation using SAS. Analyzed the dataset and partitioned it into training and validation datasets and built five different models on the training dataset- Decision trees, Interactive Decision Trees, Gradient Boosting, Logistic Regression and Neural Networks.

Big Data Analytics Using Python January 2017 - April 2017

• The objective of this project is to leverage Bigdata technologies along with data pre-processing and machine learning skills to produce meaningful insights on the chosen data. Used Hive to split the dataset into training and testing datasets and performed exploratory data analysis using Python to understand the data better. Predicted the outcomes using techniques such as Logistic Regression, Support Vector Machines, KNN classification, Decision Trees and Random Forests and used ROC curve to compare the models and selected the best model.

Business Analytics using R August 2016- December 2016

• Applied Market Basket Analysis to the transaction dataset of a supermarket and predicted which products are likely to go together thus helping the store to rearrange their product positioning.

• Performed Cluster Analysis on a dataset containing information about customers, stores and type of jeans purchased by them. This analysis helped the company to discover distinct groups in their customer base and to categorize the customers.

• Used Principal Component Analysis for datamining and reduced the dataset from 20 independent variables to 6 principal components while retaining as much of the variation present in the dataset as possible.

User Behavior analysis August 2016- December 2016

• This project is aimed at predicting the likelihood of a purchase by a customer and the repeat visits for a site in SAS using different regression techniques.

R Programming November 2016 - December 2016

• Analyzed the Movie Ratings and Movie Budgets for the years 2007-2015 by importing the dataset into R from Excel and Visualized the data using the ggplot2 function. Categorized the data according to the genre, budget and provided insights about the data which helped to derive the relation between critics rating and audience rating.

• Performed statistical operations on an organization dataset which helped them to assess their Financial Condition.

• By using t-tests, ANOVA and linear regression, identified the variables that are affecting the sales of a leading TV subscription company.

Certifications

• SAS Base Certified Programmer.

• R Programming A-ZTM : R for Data Science from Udemy.

• Python for Data Science Toolbox from DataCamp.

• Machine Learning in R from DataCamp.

• Data Manipulation and Visualization in R from DataCamp. HONORS and ORGANIZATIONS

• Awarded Dean Excellence Scholarship by Jindal School of Management. Fall 2016 – May 2017

• Event Manager for robotics event League of Machines conducted at NIT Calicut. TATHVA 2014

Contact this candidate