About
Hello! I'm Chiranjibi, a data analyst with a strong background in Statistics and Mathematics. I am skilled in analyzing big data to find trends and identify patterns using data analysis tools and techniques such as SQL, Python, R, MATLAB, STATA, and Tableau. I have always enjoyed playing with numbers and data, even going back to high school. This led me to pursue data-related passions, for example in high school, I got to know playing cards while I learned probability.
I have 3+ years of diverse experience with collecting, analyzing, and interpreting large datasets, developing new forecasting models, and performing data management tasks. I have done different projects in various domains such as banking, healthcare, e-commerce, and social campaigns.
Download my ResumeMy Skills
Python
R
SQL
Tableau
Matlab
HTML/CSS
What I do
Data Quality Assessment
As a Data Analyst, I have experience evaluating the data to determine whether the data meets the quality required for the project and business needs.
Data Analysis and Visualization
Analyzing the data and data structure and visualize them into the chart, graph to interpreting the outcomes.
Data Science and Machine Learning
I utilize my analytical, statistical, and programming skills to analyze and interpret large data sets. I build the best model and develop data-driven solutions to solve various business solutions.
My Recent Data Projects
My Publications & Certifications
Certifications
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Years Experience
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Connect Me
Healthcare Data Analysis
The purpose of this data analysis is to gain a hands-on practical experience working with healthcare data. This data is public use files derived from the Vermont Uniform Hospital Discharge Data Set for 2017. Below are the research questions I try to solve using Exploratory Data Analysis.
I also used classification algorithm decision tree to analyze the length of stay and total cost assiciated with Diagnostic.
- What is the highest and lowest cost DRG (Diagnostic Related Group)?
- What primary procedure is performed the most?
- What is the average hospital stay (in days) for inpatients?
- What is the most common primary diagnosis?
- What is the common principal payment source to pay the medical expenses?
Grocery Behaviour Recommender System
This project is based on real spending data for three months. Using this data, we applied three techniques, such as Cluster, Association, and neural network analysis. We were trying to solve the following questions.
- What are the categories and stores that we frequently purchase our daily stuffs?
- How is our buying pattern and What are the items that we most likely buy together?
- How can we optimize our spending on grocery?
Predicting Airbnb Listing Price
Airbnb pricing is important to get right, particularly in big cities where there is lots of competition and even small differences in prices can make the difference between optimum occupancy and high earnings, or being priced out of the market. It is also a difficult thing to do correctly, in order to balance the price with occupancy (which varies inversely with price) in order to maximise revenue.
This project aims to use machine learning models to predict the base price for properties, and also to explore Airbnb listing data, in order to help Airbnb hosts maximize their earnings.
Restaurant Management System
This project is about a Relational Database Management System for the management of multiple restaurants.
The goal of this relational database management system is to provide detailed information on day-to-day activities to efficiently run a profitable business as well as forecast future requirements for the management to plan on.
Predicting IMDb Rating
Film Industry is not only a industry or a centre of entertainment but also it is a centre of global business. The world is now excited about a movie's box office success, failure, popularity etc. A huge data is coming every day and available online about these movies success or popularity.
I have used hollywood movie data set and their rating from IMDb movie rating. I applied some machine learning classification algorithms such as linear regression,Random forest, KNN model. Lastly an efficient model is developed to predict a movie's IMDb rating.
Radiation Signal Detection System
This analysis uses two detectors located in Soudan Underground Laboratory to understand high energy neutron production by muons in an underground environment: a water-Cherenkov detector sensitive to high energy neutrons; and a gas-filled detector sensitive to charged particles like muons using data from both detector systems.
Analyzing Employee Turnover Problem
Understanding why and when employees are most likely to leave can lead to actions to improve employee retention as well as possibly planning new hiring in advance. I am exploring the employee dataset to solve following research questions:
- Why employee are prone to leave?
- What type of employee are prone to leave the company?
- Predict the future employee who would tend to leave the company.