Experienced and skilled IT professional with 5+ years’ experience in Data Management. Recently, completed a 6 months certification program in Data Science and Visualization from Rutgers University. Completed multiple real-life team projects in Data Science using Fundamental Statistics, Python Programming, Databases, Front-End Web Visualization, Data Visualization Business Intelligence Software, Big Data Analytics, and Machine Learning. Excellent written, verbal communication, and research skills. My analytical problem abilities combined with my strengths in collaborating across diverse groups make me a valuable addition to any team.
July 2022 - Current
March 2021 - July 2022
Jan 2021 - March 2021
Aug 2020 - Dec 2020
Extract data with API,CSV format, Text format from US Bureau of Labor Statistics, and Zillow. Transform data using Python and load data using PostgreSQL.We could identified correlation between median housing price and the effect of unemployment rates as per counties in New Jersey.
Used Feature Engineering to extract features such as Zip Code, Household, Total Rooms, and Total Bedrooms from Dataset which had Latitude, Longitude, Median Income, House-Age, Population, Average Rooms, Average Bedrooms.Identified Gradient Boosting Regression Prediction Model as the best model with 85% prediction accuracy for future price change for California Housing Dataset.
Extract data from world bank. Cleaned and compiled data using Python. Tried to figure it out possible causes of climate changes and average monthly temperature in 5 countries(India, China, Canada, Australia, Chile) over 10 years.
An interactive dashboard of belly button micro-organisms developed from a dataset of volunteer provided samples. Data is served from a Python Flask application and dynamically gathered and presented with javascript and Plotly.
Visualization of Pyber and Pymaceuticals data using MatPlotLib. Data processing was done with Pandas.
Basic climate analysis and data exploration of climate database using Python, SQLAlchemy, Pandas, and Matplotlib. Climate data has been take from OpenWeatherMap API.
This project uses D3.js to visualize some state-level data about population health based on 2014 U.S. Census data. It simulates an on-line newspaper article with an interactive visualization.
Visualization of earthquakes occurring globally using a live API feed provided by the USGS. The data in the feed is updated every 5 mins, and includes all earthquake data for the Past 7 Days.
Filter and look up UFO sightings data.
Project uses Tableau to create an interactive dashboard of CitiBike data in Jersey City, New Jersey
An analysis of weather patterns using python, the OpenWeatherMap API, and CityPy to visualize trends in temperature, humidity, cloudiness, and windiness by latitude.
A webscraping application which retrieves and presents summary information, the latest news, and images of Mars.
