Prerak Chintalwar

Well-qualified Data Analyst experienced working with vast data sets to break down information, gather relevant points and solve advanced business problems. Skilled in predictive modeling, data mining and hypothetical testing, DIPP analytics, statistics and algebraic techniques.

Certified Digital Marketing Masters Course

GDP Analysis

• The end goal of this project was to help the CMs focus on areas that will foster economic
  development for their respective states by analyzing GDP of every state and thus
  suggesting ways to improve it.
• A python based project using statistics and exploratory data analysis.
  

Telecom Churn Case Study

• Built models like Logistic Regression, Random Forest and Linear Regression with
  handling class-imbalance and performing PCA to reduce the dimensionality of the data
  set.
• A python based project to determine whether a customer will churn or not.
  

IMDB Data Analysis

• Identified the key aspects of movie success and developed an executive summary to help
  the new production company expand their business in the international movie market.
• An SQL based data analysis project which gives insights about the existing IMDB data.
  

E-Commerce Data Analysis

• Worked to draw insights from the 14GB data of e-commerce events data and identified
  the categories of products causing drastic changes in the revenue being generated.
• The analysis has been done using HDFS and Hive on the AWS platform for more efficient
  data storage and processing.
  

Lead Scoring Data Analysis

• Developed a Logistic Regression model which predicts the probability of a person to
  convert as a lead to an online education company depending upon various factors of their
  interaction.
• This analysis helps the company reduce their investment in time, money, and effort to
  the organization by narrowing the focus area to a limited number of people who are more
  likely to be converted as leads.
  

Help International

• Clustering countries based on socio-economic and health factors and recommending the
  top 5 countries to the CEO that are in direst need of aid.
• A python based machine learning project to list out top 5 countries using unsupervised machine learning approach.

Approach steps for the above projects:

1. Data Cleaning and Data Preparation

2. Performing Exploratory Data Analysis in Python and understanding in depth all the data points.

3. Creating Machine Learning Models

4. Answering the problem statement in detail, devising solutions and presenting it to the stakeholders.