Taruna Bansala

Taruna Bansala

Phone: (647) 897-0150 | Email: tarunasbansala@gmail.com | Toronto, ON, L6A0K1

LinkedIn: www.linkedin.com/in/taruna-bansala | GitHub: https://github.com/TARUNABANSALA

Summary

Highly skilled and passionate data analyst with expertise in VBA, Pandas, Python, Matplotlib, SQL, Scikit-learn, Jupyter Notebook, Tableau, and Machine Learning. Offering a strong ability to automate tasks, streamline processes, and manipulate large datasets to provide valuable insights for informed decision-making. Able to contribute to the growth of organizations through data analysis, visualization, and applying machine learning techniques, while continuously enhancing skills and knowledge.

Technical Skills

Projects

COVID-19 Analysis: "Visualizing the Pandemic" | March 2023 - April 2023

Developed an independent project that focused on the comprehensive analysis and visualization of COVID-19 data. Proficient in implementing statistical analysis techniques, including aggregation and correlation analysis.

Role: Sole Author

Tools: Utilized Pandas, Jupyter Notebook, and Matplotlib for data analysis and visualization.

GitHub Repository: https://github.com/TARUNABANSALA/COVID-19-Analysis-Visualizing-the-Pandemic-.git


COVID-19 Analysis Project: Technology Modernization | June 2023

Revitalized COVID-19 analysis via a dynamic Flask-powered API with MongoDB Atlas integration, crafting interactive Plotly, Leaflet, and Charts dashboard. Conducted in-depth mortality, population, and vaccination analysis with enhanced user engagement through intuitive menus and employed advanced NoSQL database techniques.

Role: Sole Author

Tools: Python, Flask, Plotly, Leaflet, Charts, MongoDB Atlas, HTML/CSS, JavaScript

GitHub Repository: https://github.com/TARUNABANSALA/COVID-19-Analysis-Project-Technology-Modernization-.git

Website: https://covidcanada.fly.dev


Demographic Segmentation with Census Data | July 2023 - August 2023

Leveraged Canada's census data to predict customer behavior using demographic clustering. Analyzed nationwide and provincial socio-economic demographics for future sales insights. Focused on clustering by income, exploring education, age, population, and dwelling counts. Applied unsupervised learning for targeted insights on population segments.

Role: Sole Author

Technologies: Python, Machine Learning, Pandas, Tableau

GitHub Repository: https://github.com/TARUNABANSALA/Demographic-Segmentation-with-Census-Data-.git

Education