Data Professional with over 4 years of experience in analysis, visualization, and QA. Leveraged AWS (S3, Redshift) to manage large-scale datasets, reducing data errors by 20% through automated cloud pipelines.
Increased conversion rates by 15% via A/B testing and improved decision-making efficiency by 30% with Tableau dashboards integrated with cloud sources. Proficient in SQL, Python, and Tableau within Agile environments.
Consultant Developer
Infogain- Engineered scalable software solutions using Python and Excel; enhanced productivity leading to a 50% increase in system performance and reliability.
- Optimized algorithms and data structures, resulting in a 40% reduction in processing time and improved user experience.
- Performed data validation and cleaning to ensure integrity across multiple data sources, improving report accuracy by 15%.
Languages & Tools
Analytics
Soft Skills
AWS Certified Solutions Architect
Validation: f5bf662cf15a413cab28cbc2afecd88e
Python for Everybody Specialization
Coursera — ID: U6DYBENFYMSF
The Data Science Course 2025
Udemy — ID: UC-02dac8b3-32df-43e6-9869-9a428c00570b
B.E. in Computer Science & Engineering
BMSIT & M
Linear Regression with Python
GitHub ↗Developed a linear regression model to analyze customer behavior and predict purchasing trends, contributing to a 15% increase in customer retention. Utilized Pandas and scikit-learn to improve prediction accuracy by 20%.
Voice Assistant
GitHub ↗Created a system to convert voice commands to text and vice versa, increasing app usage by 30%. Utilized speech recognition and time libraries to improve efficiency by 60%.
A/B Testing for Website Conversion
Kaggle ↗Applied a Chi-Square test for independence to analyze results, determining with 95% confidence that the new site version did not significantly increase conversion.
☁ AWS Cloud Resume Challenge
LiveBuilt and deployed this resume as a static website on AWS using S3, CloudFront, Route 53, Lambda, DynamoDB, and API Gateway — fully automated with CI/CD via GitHub Actions.