Kiran Ranganalli

Data Enthusiastic

ABOUT ME

Hi, I’m Kiran Ranganalli, a data analyst with over three years of experience in data analytics, business intelligence, ETL pipeline development, and data engineering. I hold a Master’s in Business Analytics and have worked across insurance, e-commerce, and fintech, driving data-driven decision-making through advanced analytics, automation, and strategic reporting.

In my previous roles, I have worked on fraud detection, risk analysis, customer segmentation, KPI tracking, and predictive modeling. At Capgemini, I built fraud detection analytics for an insurance client, automating ETL workflows for 1.7M+ policy records, improving fraud detection by 35%, and increasing retention by 40%. At Delivered Korea, I optimized marketing analytics, increasing ad engagement by 25% and improving budget allocation by 18%.

My expertise includes SQL, Python, Power BI, Tableau, AWS (S3, Glue, Redshift, QuickSight), and data warehousing. I have built and optimized ETL pipelines, automated reporting workflows, and designed scalable data models to improve operational efficiency and support business growth.

With hands-on experience in big data processing and cloud computing, I have worked extensively with Apache Spark, Apache Airflow, Snowflake, AWS, Microsoft Azure, and Google Cloud Platform. My technical background also includes A/B testing, statistical modeling, risk analytics, and machine learning techniques (Scikit-Learn, XGBoost, TensorFlow, PCA, K-Means Clustering).

Education

Masters of Science
Business Analytics
San Francisco State University

2023-2024

GPA - 3.6

Bachelors of Technology

Electronics & Instrumentation

VNR Vignan Jyothi Institute of Technology

2015-2019

GPA - 3.2

Professional Experience (3+ Years)

Delivered Korea

Data Analyst Intern

San Francisco, California.

2024

Developed KPI-driven ad performance dashboards, tracking digital marketing campaigns and e-commerce traffic sources, providing real-time insights into campaign reach, engagement, and return on investment (ROI). These dashboards optimized budget allocation, improved customer acquisition strategies, and increased conversion rates by 18%
Analyzed purchasing trends, leveraging AWS analytics, Amazon QuickSight, and MongoDB, to build customer segmentation models that improved marketing campaign effectiveness by 25% and increased customer retention by 15%. These models provided business teams with insights into consumer behavior, seasonal demand fluctuations, and targeted product promotions
Drove cross-functional discussions, presenting customer insights and ad performance analytics to marketing, data, and business teams, aligning findings with strategic objectives. Ensured data-backed decision-making by collaborating with stakeholders, refining advertising strategies, and optimizing marketing spend across various customer acquisition channels

Capgemini

Data Analyst

Bangalore, INDIA.

2020-2023

Developed interactive KPI dashboards in Power BI and Amazon QuickSight to track claims performance, policy renewals, and fraud detection metrics, automating real-time reporting and improving strategic decision-making by 35% for underwriting teams. These dashboards provided actionable insights to help identify fraud patterns, reduce policy lapses, and optimize claims management
Designed and optimized ETL workflows to transform claims and billing data, ensuring high-quality datasets for risk analysis. Implemented data pipeline automation using Apache Airflow and PySpark, reducing data processing time by 45% and ensuring seamless integration between Snowflake and SQL Server databases
Drove stakeholder discussions, analyzing billing discrepancies and fraud risk trends, collaborating with finance, compliance, and risk analysts to refine policy pricing models and implement fraud detection measures. Provided data-driven insights that helped reduce claim processing time by 20% and improve billing accuracy
Performed advanced churn analysis, examining 6 lakh+ policy records to identify customer lapse risks and enhance retention strategies. Built predictive models to assess policyholder behavior, allowing underwriting teams to implement targeted engagement strategies that improved policy renewal rates by 40%
Collaborated across cross-functional teams, including finance, compliance, and risk analysts, to enhance data governance, reporting automation, and regulatory compliance tracking. Streamlined reporting processes by implementing automated data validation workflows, increasing operational efficiency and reducing manual intervention

INCOIS(Indian National Center for Ocean Information Services)
Internship
Hyderabad,India

2018

Cleaned and organized geospatial datasets using Python, SQL, and Excel, improving data accuracy by 30% for marine research and coastal mapping
Conducted correlation analysis between coral reef abundance and fish populations in the area, leveraging geospatial modeling and predictive analytics to support marine ecosystem research
Developed interactive geospatial visualizations using Python (Matplotlib, Seaborn) and GIS tools, enabling marine scientists to track ecosystem changes more efficiently, improving data accessibility and reporting by 25%

Certification

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The AWS Certified Data Engineer – Associate (DEA-C01) certification enhances my ability to design and manage scalable, efficient, and cost-optimized data pipelines in cloud environments. By leveraging AWS services like S3, Glue, Redshift, Kinesis, and Athena, I can streamline ETL workflows, automate data processing, and improve real-time analytics. This certification strengthens my expertise in big data handling, performance optimization, and secure data management, allowing me to build faster, more reliable, and scalable solutions that drive better decision-making and operational efficiency.

Certification

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Achieving the Google Data Analytics Certificate from Coursera has significantly enhanced my ability to tackle complex business challenges using data-driven insights. This certification provided hands-on training in tools like SQL, R, and Tableau, enabling me to collect, clean, and analyze data efficiently. It also strengthened my understanding of visualization techniques and statistical methods, which are essential for identifying trends and patterns that drive strategic decision-making. By applying these skills, I’ve been able to contribute to optimizing business operations, understanding customer behaviors, and delivering actionable insights that support sustainable growth in my data analysis journey.

Projects

Capstone

Delivered Korea

Conducted a comprehensive analysis of Delivered Korea's Shopify dataset to identify characteristics of high-value and low-value customers. Utilized statistical methods and data modeling to uncover spending behaviors and provide actionable business insights for strategic decision-making.

PowerBI

Pizza_Sales

Analyzed pizza sales data using Power BI to create interactive dashboards that highlighted sales trends, top-performing products, and customer preferences, enabling data-driven decision-making for business optimization.

Machine Learning

Credit card fraud detection

Developed a machine learning solution for credit card fraud detection using a Kaggle dataset. Applied techniques such as data preprocessing, SMOTE for handling class imbalance, and predictive modeling with Logistic Regression, Random Forest, and XGBoost to identify fraudulent transactions with high accuracy, enhancing financial security.

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HealthCare

Health Data Analysis

This project analyzes a healthcare dataset to uncover insights such as patient demographics, common medical conditions, doctor-specialty associations, and hospital performance. It includes data visualizations and ranking analyses to support healthcare decision-making.

Customer Sales

E-Commerce Customer Analysis: Insights and Strategies

This project analyzes an e-commerce dataset to uncover customer behavior patterns, revenue drivers, and churn risks. By applying advanced data analytics techniques such as clustering, predictive modeling, and exploratory data analysis, the project delivers actionable insights to optimize business strategies, enhance customer retention, and improve overall operational efficiency.