My academic journey has equipped me with a robust understanding of computer science fundamentals and data analysis techniques. During my time as a Test Engineering Analyst at Accenture, my analytical mind thrived. However, I yearned to delve deeper and uncover hidden insights within data.
This curiosity led me to pursue a Master's in Business Analytics. My academic excellence was recognized as I was nominated as one of the most outstanding business students and invited to join Beta Gamma Sigma (BGS). This experience further solidified my desire to leverage data for impactful decisions.
Equipping myself with Python, SQL, and a passion for impactful decisions, I'm eager to transition my analytical skills and problem-solving abilities to the data science domain. I'm confident that my computer science background, combined with my business acumen, will allow me to learn quickly and contribute meaningfully to data-driven solutions.
Seasoned consultant with a strong passion for data science. Recognized for leveraging analytical acumen to inform strategic business decisions. Eager to apply these skills and contribute to your team’s success.
As a part of my capstone, I collaborated with JHI, a finance company, to enhance their client tiering model.
Worked as a consultant for five years at Accenture, specializing in improvising financial products.
GPA: 3.97/4.00
GPA: 3.73/4.00
GPA: 3.15/4.00
I'm thrilled to showcase a selection of projects I've undertaken, both during my academic pursuits and beyond.
Leveraged Python's popular data analysis libraries, Pandas and NumPy, to analyse the Friends TV show dataset from Kaggle. Employed Matplotlib and Seaborn data visualization libraries to generate insightful graphs.
Leveraged R's powerful machine learning libraries such as tidymodels and Tree to predict customer purchase behavior. Compiled all analyses into an interactive dashboard for seamless data consumption.
Collaborated in a team to analyze Amazon's bestselling books (2009-2019) using NLP techniques (NLTK) to uncover dominant themes and genres, along with positive and negative sentiment trends in book titles.
In this project, I delved into the world of song lyrics using R, employing Tidy verse to tidy up the data and prep it for analysis. I roped in topic modeling to figure out the main themes running through the lyrics. Did sentiment analysis and brought in a network diagram to tell a story.
In this project we delve into the fascinating world of domestic flight ticket pricing in India. Utilizing the Data Analysis Toolpak in Excel, we employed regression modeling techniques to uncover the key factors influencing airfare.
Below are the details to reach out to me!