PAWANKUMAR ARAGANJI

Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in Aircraft Maintenance.

Organized with successful history of managing competing priorities and meeting challenging performance targets. Works well under pressure to complete physically-demanding work. Safety-oriented team player with strong attendance record.

1) Recommending ways to increase revenue of a Grocery Store

Skills and Tools : Market Basket Analysis, Exploratory Data Analysis, KNIME, Python

• The project entails doing a detailed study of Point of Sale (POS) Data in order to provide advice on how a grocery shop may enhance its income by creating appealing combination and discount offers for customers.

2) Understanding Customers' Buying Patterns for an Automobile Parts Manufacturer

Skills and Tools : RFM, Exploratory Data Analysis, Python, KNIME

• This project attempts to discover the underlying buying habits of an automobile part manufacturer's consumers using transaction data from the last three years, and to develop personalized marketing tactics for distinct client categories.

Skills and Tools : Joins, Sub Queries, SQL-clauses-statements-conditions, SQLite using DB Browser and MySQL Workbench

• This project is based on the order administration feature of an online retail company, and you are given the "orders" database and asked some questions about it.
• The answers to these questions will assist the organization in making data-driven decisions that will have an influence on the overall success of the online retail shop.

4) Visualizing Insurance Claims using Tableau

Skills and Tools : Business Intelligence, Tableau, Dashboard Designing

• This study used visual analytics to investigate the art of problem solving.
• Tableau's data visualization capabilities were utilized to construct interactive dashboards that provided high-level insights to an insurance company's CEO in order to influence policymaking.

5) Built a model to Forecast monthly sales of Wine for certain Wine Estate for the next 12 month

Skills and Tools : Exploratory Data Analysis for Time Series Data, Exponential Smoothing Models, ARIMA/SARIMA Models, Moving Average Models

• A company's previous monthly sales data was examined.
• Created various prediction models for two distinct Wine Estate products and selected the best forecasting model to anticipate monthly sales for the next 12 months, along with suitable lower and higher confidence levels.

6) Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning

Skills and Tools : Text Mining Analytics, Support Vector Machine - K Nearest Neighbor - Naive Bayes, Ensemble Techniques, Logistic Regression - Linear Discriminant Analysis

• This project is built on two case studies: voter prediction and text analysis.
• The first project aims to forecast which party a person would vote for based on their age and the responses given by the voters to the questions posed in a survey.
• The second research is based on an examination of the inaugural presidential addresses in the United States of America. Based on the examination of these talks, one must draw conclusions.

7) Gems & Holiday Package Prediction

Skills and Tools : Linear Regression, Logistic Regression, Linear discriminant Analysis

• This research is built on two case studies: gem price prediction and vacation package prediction.
• In the first case study, linear regression ideas are tested, and the student is asked to forecast the price of gems based on several variables in order to assist the organization optimize profits.
• The ideas of logistic regression and linear discriminant analysis are evaluated in the second scenario. To target the suitable client base, one must estimate if the buyer would purchase the vacation package.

8) Bank Customer Segmentation and Insurance Claim Prediction

Skills and Tools : Clustering, CART, Random Forest, Artificial Neural Networks

• The study required generating conclusions from two case studies: bank marketing and insurance.
• To derive conclusions from these case studies, the concepts of Clustering, CART, Random Forest, and Artificial Neural Network are applied.
• Various performance indicators have been used to assess prediction performance on Test and Train sets.

9) Salary Analysis using ANOVA and Principal Component Analysis on College Admissions Data

Skills and Tools : ANOVA, EDA, PCA

• The study required deriving conclusions from two case studies: salary analysis and college admissions data.
• To derive conclusions from these case studies, the principles of exploratory data analysis, analysis of variance, and principal component analysis are applied.

10) Statistical & Probabilistic Analysis of Store Sales, University Survey, & Manufacturing data

Skills and Tools : Descriptive Statistics, Probability, Estimation, Hypothesis Testing

• The study required extracting conclusions from three case studies: wholesale customer data (store sales), university survey data, and manufacturing shingles data.
• These case studies are analyzed using the principles of Descriptive Statistics, Probability and Probability Distributions, and different Estimation and Hypothesis Testing techniques.

11) Uber Drive

Skills and Tools : Python Functions, Data Interpretation

• The project is based on Uber driver journeys.
• Various Python functions are used to examine various parts of the journey.

1) Recommending ways to increase revenue of a Grocery Store

Skills and Tools : Market Basket Analysis, Exploratory Data Analysis, KNIME, Python

• The project entails doing a detailed study of Point of Sale (POS) Data in order to provide advice on how a grocery shop may enhance its income by creating appealing combination and discount offers for customers.

2) Understanding Customers' Buying Patterns for an Automobile Parts Manufacturer

Skills and Tools : RFM, Exploratory Data Analysis, Python, KNIME

• This project attempts to discover the underlying buying habits of an automobile part manufacturer's consumers using transaction data from the last three years, and to develop personalized marketing tactics for distinct client categories.

3) Online retail Orders Analysis

Skills and Tools : Joins, Sub Queries, SQL-clauses-statements-conditions, SQLite using DB Browser and MySQL Workbench

• This project is based on the order administration feature of an online retail company, and you are given the "orders" database and asked some questions about it.
• The answers to these questions will assist the organization in making data-driven decisions that will have an influence on the overall success of the online retail shop.

4) Visualizing Insurance Claims using Tableau

Skills and Tools : Business Intelligence, Tableau, Dashboard Designing

• This study used visual analytics to investigate the art of problem solving.
• Tableau's data visualization capabilities were utilized to construct interactive dashboards that provided high-level insights to an insurance company's CEO in order to influence policymaking.

5) Built a model to Forecast monthly sales of Wine for certain Wine Estate for the next 12 month

Skills and Tools : Exploratory Data Analysis for Time Series Data, Exponential Smoothing Models, ARIMA/SARIMA Models, Moving Average Models

• A company's previous monthly sales data was examined.
• Created various prediction models for two distinct Wine Estate products and selected the best forecasting model to anticipate monthly sales for the next 12 months, along with suitable lower and higher confidence levels.

6) Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning

Skills and Tools : Text Mining Analytics, Support Vector Machine - K Nearest Neighbor - Naive Bayes, Ensemble Techniques, Logistic Regression - Linear Discriminant Analysis

• This project is built on two case studies: voter prediction and text analysis.
• The first project aims to forecast which party a person would vote for based on their age and the responses given by the voters to the questions posed in a survey.
• The second research is based on an examination of the inaugural presidential addresses in the United States of America. Based on the examination of these talks, one must draw conclusions.

7) Gems & Holiday Package Prediction

Skills and Tools : Linear Regression, Logistic Regression, Linear discriminant Analysis

• This research is built on two case studies: gem price prediction and vacation package prediction.
• In the first case study, linear regression ideas are tested, and the student is asked to forecast the price of gems based on several variables in order to assist the organization optimize profits.
• The ideas of logistic regression and linear discriminant analysis are evaluated in the second scenario. To target the suitable client base, one must estimate if the buyer would purchase the vacation package.

8) Bank Customer Segmentation and Insurance Claim Prediction

Skills and Tools : Clustering, CART, Random Forest, Artificial Neural Networks

• The study required generating conclusions from two case studies: bank marketing and insurance.
• To derive conclusions from these case studies, the concepts of Clustering, CART, Random Forest, and Artificial Neural Network are applied.
• Various performance indicators have been used to assess prediction performance on Test and Train sets.