Venkata Kavya Yerra - Data Analyst

Summary

Data analysis professional prepared to deliver impactful insights and drive business decisions. Adept in data visualization, statistical analysis, and database management, with strong focus on teamwork and adaptability. Known for reliability, analytical thinking, and results-driven approach. Skilled in Python, SQL, and Excel, ensuring robust data solutions and strategic recommendations.

Overview

2

years of professional experience

2045

years of post-secondary education

Work History

Data Analyst

Wipro

01.2021 - 01.2023

Utilized Engineered ETL processes using SQL and Python to systematically extract, transform, and load over 500,000 records from diverse banking systems while ensuring data accuracy reached a consistent level of 98% across platforms
Developed and implemented predictive models using Python and machine learning techniques, such as logistic regression and decision trees, to assess credit risk and predict loan defaults, resulting in a 15% reduction in loan default rates
Applied anomaly detection methods in Python to analyze transactional data, successfully identifying and mitigating fraudulent activities, which contributed to a 20% decrease in fraud cases
Designed and automated interactive dashboards and performance reports using Tableau and Power BI, providing real-time insights into critical KPIs including loan performance, customer behavior, and financial trends
Partnered with cross-functional teams (e.g., marketing, risk, finance) to deliver actionable data insights, enhancing business strategies and driving data-informed decision-making
Automated the generation of compliance reports to align with industry standards such as GDPR, Basel III, and AML/KYC, improving audit efficiency and ensuring timely and accurate reporting.

Education

M.S. - Information Systems

Pace University

New York, NY

05.2001 - 05.2024

B.tech. - Electrical and Electronics Engineering

Malla Reddy Engineering College

India

06-2021

Skills

Programming Languages: Python, R, SQL, Java, HTML, CSS

Database/Warehousing: Oracle, PostgreSQL, MongoDB

Data Engineering/Big Data Tools: PySpark, Spark SQL, Snowflake, Data Warehousing

Machine Learning/Analytics: Regression, XGBoost, Gradient Boosting, Pandas, NumPy, Matplotlib, ggplot2, SciKit-Learn

Business Intelligence Tools: Tableau, Power BI

Project Management: Jira, Microsoft Office Suite

Timeline