2022 - 2024
Masters Degree in Statistics and Data Science
California State University - East Bay
- Home
I am Maduvanthi (Maddie) a young graduate from Cal State with Masters in Statistics and Data Sciences. “To improve is to measure” and I believe that statistics and data science enables us to do so.
My love for predicting future trends and outcomes has pushed me in mastering statistical analysis, machine learning, and data visualization by executing projects in this space.
- About
Every great Analysis begins with a passion
Since the start, I have always been passionate about working with numbers and data, which led me to Data Science. I am a Masters graduate from California State University East Bay. My professional journey includes valuable experiences such as internships at Robert Bosch as an IoT data analyst, where I’ve had the opportunity to apply my skills in real-world settings. I have worked with R, Python, SPSS, Tableau, and SQL for the past five years. I’m confident, naturally curious, and perpetually working on improving and translating data into actionable insights to empower organizations. Just like Andrew McAfee said, ‘The world is one big data problem.’
Education & Experience
2022 - 2023
LASERBEAM SOFTWARE
HR Data Analyst
June 2022 - August 2022
Robert Bosch
IOT Data Analyst
2018 - 2021
Bachelor Degree in Statistics
J.B.A.S College for Women
My Skills
R
Python
Power BI
Excel
SQL
Tableau
Featured Projects
In car price analysis, Multiple Linear Regression uncovers complex relationships between variables and prices. By eliminating insignificant predictors with p-values over 0.05, refining parameters, and validating against regression assumptions, the model ensures reliability. This strategic approach offers crucial insights for decision-making in the automotive sector.
Credit Card Fraud Detection Analysis -Python
In cybersecurity, the Credit Card Fraud Detection Problem involves modeling historical transactions to identify fraud. Using Python, the goal is to develop a precise model detecting new fraudulent transactions with a 100% accuracy rate, while minimizing false positives. This reinforces financial system security with advanced analytics.
