Establishing myself in the world of
Data

Skills

Python

90%

R

80%

Statistics

70%

Experience

 
 
 
 
 
June 2018 – December 2018
Atlanta, Georgia

Intern, Research and Analytics

CNN

Responsibilities include:

  • Collect and analyze multiplatform television data across various sources, such as CNN linear TV data, VOD, SVOD, and digital.
  • Aid Research Analysts in the production of daily and regular reporting needs for the CNN brand as well as competitive networks
  • Extract and analyze Nielsen audience delivery data using a variety of research software (Ex: Nielsen NPower, Arianna, Star Media)
  • Assist team with ongoing projects, data visualizations, client presentations (in Microsoft Excel, Microsoft PowerPoint).
  • Assist in the development of a machine learning model to forecast the delivery of HLN based on historical data and other parameters.
 
 
 
 
 
August 2017 – April 2018
Atlanta, Georgia

Graduate Research Assistant

Georgia State University

Responsibilities include:

  • Investigated the influence of deployment of Electronic Medical Records (EMRs) on medical care with an aim to find if cloud-based EMRs lead to an inferior quality of care than their on-premise counterparts.
  • Web-scrapped EMR data in R using Httr, Rvest, and Tidyverse packages and linked it to the Federal Meaningful Use program data.
  • Analyzed the relationship between crowdfunding and productivity by linking data from multiple sources to determine the influence of income of a YouTube-r from the former on the success of his YouTube channel.
  • Developed a web crawler using Beautiful Soup and Urllib packages in Python to scrape and build datasets.
 
 
 
 
 
June 2016 – May 2017
New Delhi, India

Intern

National Institute for Smart Government

Responsibilities include:

  • Worked on a project to digitize and analyze Ministry of Corporate Affairs’ corporate data obtained over the years.
  • Made metadata of e – forms then extracted the data into Excel, summarized their characteristics and visualized using Tableau.
  • Assisted in building an in-house Collaboration Tool with database, email, chat and project management features using Java.

Projects

*
All Python R Machine Learning Deep Learning

Detect and count the number of tree logs in the images of trucks.

Created a model to generate realistic restaurant reviews

Separate suspicious money laundering alerts to true positives and false positives

Predict the taxi trip duration between any two points in the city of New York

A study on the public opinion about the topic ‘Bitcoin’ during it’s rise in December 2017
Code

Performed a study to establish a relationship between customer sentiments in online reviews and customer ratings for hotels.
Code

Flight delay prediction based on weather and historical data.
Code

Built an optimization model to select players for a cheap and best premiere league team
Code

Coursework

Taken during my masters program

I have taken the following courses during Data Analytics masters at Georgia State University

  • Semester 1:
    • MSA8040: Database Management for Analytics
    • MSA8010: Data Programming
    • MSA8190: Statistical Foundations for Analytics
  • Semester 2:
    • MSA8050: Scalable Data Analytics
    • MSA8200: Econometrics for Analytics
    • MSA8150: Machine Learning
    • MSA8100: Operations Research Models and Methods
  • Semester 3:
    • MSA8600: Image Analytics
    • MSA8395: Deep Learning
    • MSA8770: Text Analytics

I have also taken the following Data Science MOOCs:

  • Data Science Specialization - Johns Hopkins University (Coursera)
    • The Data Scientist’s Toolbox
    • R Programming
    • Getting and Cleaning Data
    • Exploratory Data Analysis
    • Regression Models
  • Applied Data Science with Python Specialization - University of Michigan (Coursera)
    • Applied Text Mining in Python
  • Intro to Python for Data Science Course (DataCamp)
  • Google Analytics for Beginners (Google Analytics Academy)

Tags

Contact

  • 404 509 9301
  • gundasandeep95
  • 508 Main St NE, Atlanta, Georgia, 30324, USA
  • Weekdays 10:00 to 17:00
    Otherwise email to book an appointment