Data analyst

Collect, process, analyse and present data - from supporting everyday business decisions to driving global change.

About me.

Hello and welcome to my portfolio website! My name is Sunil Goroji and I am a data analyst with a passion for exploring and interpreting complex data sets.
My interest in data analysis began during my undergraduate studies where I was exposed to various statistical concepts and data manipulation techniques. After graduation, I pursued a career in data analysis and have since honed my skills in data cleaning, data visualization, and statistical modeling.
I have experience working with large data sets from diverse industries such as sales, finance, and marketing. My primary goal as a data analyst is to translate complex data into actionable insights that can inform business decisions and drive growth.
In my work, I prioritize the use of industry-standard tools such as Python, SQL, and Tableau to ensure the accuracy, efficiency, and reproducibility of my analyses.
Aside from my technical skills, I am a strong communicator and collaborator who enjoys working with cross-functional teams. I am always eager to learn new skills and stay up-to-date with the latest trends in the data analysis field.
Thank you for visiting my portfolio website and I hope my work here showcases my passion and skills in data analysis.

Customer analytics:
Virtual Internship

Completed a four-week virtual internship with KPMG, gaining hands-on experience in data analysis, customer segmentation, and predictive modeling. Conducted EDA on customer demographic and transaction data for customer targeting.

Capstone Project:

Collecting, analyzing and visualizing data about a ficticious company called Cyclistic to give recommendations on some great advertizing strategies.

Finance Data Analysis:

This data project focus on exploratory data analysis of stock prices. Which focus on 7 popular bank stocks and see how they progressed throughout the financial crisis which occured in the early 21st century.

Web Scraping:
GitHub topics and Repos.

scraping the GitHub topics and their popular repositories with most star counts, using python libraries like requests and bs4 (BeautifulSoup) and storing that data in a file.

Data Science Job-salaries:

Analyzing and visualizing dataset already avilable in Kaggle to chech how the fields in the Data Science are paid differently.

sql-challenge 1:
Danny's dinner

Querying the simple dataset about a fastfood company to answer some questions about customers and their visiting patterns .