GitHub - amanjot-git/amanjot-git

Amanjot Kandhola

Data Analyst | Salesforce, SQL, Python, Pandas, Data Visualization | Taught Coding languages

Data Science - University of Waterloo and University of Toronto
Masters of Computer Science Engineering - Chitkara University, India

Current job: Data Analyst at Nonprofit Serving Individuals with Visual Impairments

Hi 👋

As a data analyst at CNIB, a nonprofit organization dedicated to supporting individuals with visual impairments, I bring a Masters of Engineering in Computer Science and over 10 years of experience in teaching coding languages and bringing data analytics to the table.

Driven by an insatiable curiosity and a solid foundation in critical thinking, my career has been centered around solving complex problems. I specialize in using SQL and Python for tasks ranging from data collection and wrangling to analysis and visualization, ensuring that insights are not only comprehensive but also accessible to all.

In summary, I offer a unique combination of technical expertise, problem-solving skills, and a dedication to serving our community. My proficiency in utilizing the Python data science software ecosystem enables me to provide valuable insights and drive meaningful change through data analysis, visualization, and effective communication.

Currently enrolled in Data Science program by University of Waterloo and University of Toronto

🎓My Learning - Experience Journey

Data Science - University of Toronto and University of Waterloo ('24)
Google Data Analytics ('22)
Master of Engineering in Computer Engineering - Chitkara University ('16)
Bachelor of Engineering in Computer Engineering - Chitkara University ('13)

🌱 My latest projects

From Energy to Health: Data Science Insights Across Diverse Domains In my journey as a data scientist, I’ve had the opportunity to work on diverse projects that span energy management, financial risk, probability puzzles, behavioral science, and healthcare. Each project has allowed me to apply advanced data processing, statistical inference, machine learning, and simulation techniques to generate actionable insights. Here’s an in‐depth look at these projects and the methodologies I used to drive impactful business outcomes.

Powering Insights: Energizing Customer Segmentation Through K-Means Clustering
Credit Crunch Classifiers: Tuning Random Forest & KNN for Default Prediction
The Winning Switch: Unraveling the Monty Hall Paradox via Simulation
Buzzing Differences: Beer vs. Water in Mosquito Attraction Revealed
Risk, Rewards, and Returns: Statistical Inferences in Finance and HR
Linear Logic: Transformations, Diagnostics, and the Art of Regression
Health Under the Lens: Data-Driven Insights in Diabetes Risk & Prevention

Each of these projects reflects my commitment to leveraging data science to drive actionable insights across varied domains. Whether optimizing energy consumption, predicting financial defaults, solving classical probability puzzles, investigating behavioral phenomena, or advancing healthcare outcomes, my approach is centered on thorough data preprocessing, rigorous statistical testing, and thoughtful model evaluation.

By combining these methodologies, I have been able to provide stakeholders with clear, data-driven recommendations that not only improve operational efficiency but also enhance risk management and preventive healthcare strategies. I am excited to continue exploring new challenges and harnessing the power of data to transform insights into impactful actions.