I hold a Bachelor's degree in Software Engineering from Carleton University, Canada and I recently completed a Data Analytics graduate certificate from George Brown College, Toronto.
I am a self-starter who enjoys Math, working with numbers and analyzing datasets to extract and visualize key insights to answer business-related questions and make data-driven decisions. I have been constantly honing my skills in data analysis through personal projects and volunteering.
Recently, I volunteered at an early-stage startup as a marketing and analytics team lead, where I experienced how a data-driven approach can lead to increased efficiency and positive results. This made me realize how important and powerful data is in making decisions in an organization and motivated me to become a Data Analyst. I currently volunteer as a data analyst at Data for Good and recently worked as a data analyst intern at PointVerge Ltd.
I love taking numbers and raw data and turning them into meaningful and actionable insights! Proficient in SQL, Advanced Microsoft Excel, Python, Microsoft Power BI and Tableau. Proven expertise in data analysis, visualization, reporting, statistical analysis, and machine learning algorithms.
Below are the some of my Data Analytics projects using SQL, Python, Tableau & Excel.
This analysis project investigates and gains insights into the major factors impacting the bank's customer churn rate using Python. Subsequently, the study aims to provide recommendations to the bank, thereby facilitating a reduction in churn rate and improving customer retention. In addition, a machine learning model is deployed to accurately predict customer churn.
Sprocket Central Pty Ltd has given KPMG a list of 1000 potential customers with their demographics and attributes. However, these customers do not have a prior transaction history with the organization. The objective of this project is to analyze the existing customer and transactions data to reveal useful customer insights that could help optimize resource allocation for targeted marketing by selecting top target customers from the list of potential customers.
The objective of this research is to investigate the factors surrounding the purchase behaviour of frozen potatoes in the retail market and devise a Marketing strategy to improve client retention and foster trust and loyalty among existing customers while attracting new clientele seeking a customer-centric experience.
This project visually analyzes a customer data using Tableau. The following key metrics are analyzed: Total revenue per state, Total revenue per category by gender, Total sales by category, Percent revenue by region, Total sales by age, Total revenue by gender, Total revenue per month and the Discount-Quantity correlation.
This project involves the cleaning and analysis of a Nashville housing dataset using SQL to derive insights for stakeholders in the real estate domain. The dataset, consisting of 56,477 records, encompasses various attributes such as land use, sale prices, property details, and ownership information.
This project performs Exploratory Data Analysis (EDA) using Python and SAS on the happiness rate of countries based on attributes such as happiness score, social support, GDP per capita, family, life expectancy, perceptions of corruption, etc. and analyzes the effect of COVID-19 on the individual attributes as well as the overall happiness of countries.
Below are the details to reach out to me!
Toronto, Canada