Data Scientist Intern
Data Scientist Intern with a B.Tech in Computer Science and Engineering, where I leverage my skills in data analysis and machine learning to solve complex business problems. I have successfully completed the Entri Elevate Program by the Illinois Institute of Technology, gaining certification in Data Science and Machine Learning. My expertise includes web scraping, data cleaning, preprocessing, visualization, building and deploying machine learning models, and statistical analysis. I am proficient in Python and SQL, and experienced with tools like PowerBi, Openrefine, Metabase, jupyter notebook, Scikit-learn,matplotlib, numpy, Playwright, Beautifulsoup, Seaborn, Pandas etc.. Passionate about innovation and data-driven decision-making, I am eager to connect and explore opportunities in the data science field.
Datahut
-Collaborated closely with senior data scientists to understand project requirements and tasks. -Led data collection efforts through web scraping, ensuring accuracy and completeness of datasets. -Maintained detailed code documentation for all projects, following best practices in version control. -Conducted data cleaning processes to ensure high-quality datasets, addressing missing values, outliers, and inconsistencies. -Performed exploratory data analysis (EDA) to uncover trends, patterns, and insights within datasets. -Created comprehensive EDA documentation to support data-driven decision-making.
A collaborative project which is developed and published in PyPi. It is a Python package designed for testing user agents on specific websites. It helps in identifying which user agents are effective for web scraping or automated testing by filtering out those that work or fail.
python · requests · beautifulsoup
Data science and Machine Learning project where I implemented predictive modeling to optimize the supply chain for a Fast Moving Consumer Goods (FMCG) company, focusing on aligning demand and supply to reduce costs and enhance profitability. Conducted thorough Exploratory Data Analysis (EDA) and developed machine learning models, achieving competitive Mean Squared Error (MSE) scores and R-squared metrics.Identified key features influencing demand-supply dynamics, contributing to informed decision- making. Technologies utilized include Python, Scikit-Learn, Seaborn,NumPy, Pandas and Matplotlib.
python · Scikit-Learn · Seaborn · NumPy · Pandas · Matplotlib · Machine Learning Algorithms · data cleaning · data analysis
For my portfolio project in Power BI, I undertook the development of a dynamic dashboard utilizing the New York City Airbnb open dataset. Utilizing Power BI's rich suite of tools and visualizations, I crafted an engaging interface showcasing key metrics such as listing prices, occupancy rates, and geographical distribution of properties. Through in- depth analysis of guest reviews, host information, and property amenities, I provided actionable insights for both hosts and guests to enhance their Airbnb experience. This project exemplifies my proficiency in data exploration, visualization, and leveraging Power BI to deliver impactful insights in the hospitality industry.
power bi · dax · data visualisations · data analysis
web scrapping, data collection, data cleaning, Exploratory Data Analysis, Machine Learning, data visualisation, Power Bi, Metabase, seaborn, Matplotlib, plotly, basics in excel, scrapy, playwright, beautifulsoup, scrapy-playwright, python programming, sqlite, mysql, requests, Technical Documentation, Data Analysis, OpenRefine, Postman Api, Proxy Servers, Data Modeling, Microsoft Visual Studio Code, Jupyter Notebook, Self learner, Attention to Detail, Teamwork, Quik Learner, Programming skills, Power Point Presentations
B.tech in Computer Science