Data Analyst Business Intelligence

Kiran Kaushal Kotha

*****.*****@****.*** +* ***(*00)6354 www.linkedin.com/in/kiran-kaushal-kotha

Education

M.S. Business Analytics North Dakota State University GPA 3.4/4 Aug 2023 – May 2025

B.E Civil Engineering Anna University CGPA 7.37/10 Apr 2016

Summary

Enthusiastic Data Analyst with 5 years of expertise in statistical analysis, specializing in fraud detection, and business intelligence. Proven ability to extract, analyze, and structure large datasets to drive data-driven decision-making and optimize operational efficiency. Experienced in designing interactive Tableau dashboards and automating SQL-based reporting workflows to improve accuracy and business performance.

Work Experience

Google Operations Center - Community Manager/Analyst for Google Play(EN) Jul 2021 – Jul 2023

Managed and analyzed beta testing data for Google Play Games on PC (Q3 2021), leading a global team of 10 Product Experts. Designed data-driven reports and optimization frameworks that enabled Product Managers to enhance customer engagement, increasing satisfaction from 8% to 60% over two years

Developed a high-impact keyword database of 1,200+ terms and leveraged it to build interactive Tableau dashboards, enabling real-time analysis of backlog trends, community metrics, and content classification, which improved reporting accuracy and supported strategic decision-making.

Designed and automated workflows for thread classification, leveraging keyword analysis to filter out generic threads, reducing the active workload by 35%. This allowed Product Experts to handle common queries, enabling the team to focus on high-priority issues, streamline operations, and improve overall efficiency, contributing to a 10% YoY growth in community KPIs.

Conducted SQL and keyword-based fraud pattern analysis, triggering an internal Safe Team investigation. This resulted in the removal of 300+ fraudulent loan apps, reducing platform risk exposure and enhancing digital security for millions of users.

Led weekly hangouts with Product Experts (PEs), fostering engagement and motivation by recognizing their contributions, which enhanced productivity by 7% per quarter.

MarketStar - Google Ads Analyst/ Campaign Performance Analyst Jan 2020 – Jul 2021

Analyzed campaign performance data across 150+ Google Ads clients per quarter, applying advanced segmentation, and predictive analytics to optimize ad spend. Implemented targeted keyword strategies that improved average ROI by 125%

Conducted in-depth data analysis on advertiser business models, audience segmentation, and market trends, leading to custom ad strategies that increased CTR, CPC efficiency, and conversion rates by 18%.

Utilized Google Analytics to assess user engagement, bounce rates, and session durations, refining ad placements and boosting ad performance, audience retention, and improving client satisfaction by 20%.

Partnered with Google My Business team to identify unregistered businesses appearing on Google. This effort helped combat fraudulent business masking, where unauthorized entities used legitimate business credentials to operate illegally.

Designed and implemented streamlined workflows for campaign creation, integrating automation and data insights to reduce manual effort and cut time-to-market for new advertising initiatives by 30%.

Amazon - Seller Support Associate/ Fraud Detection May 2017 – Sep 2019

Analyzed recurring payment discrepancies and recommended process optimizations, resulting in a 20% reduction in resolution time and enhanced fraud detection efficiency.

Leveraged Amazon’s fraud detection systems to analyze high-volume transactions, identifying suspicious patterns and improving chargeback resolution by 98% within SLA.

Partnered with sellers to implement proactive fraud prevention policies, leading to a 15% reduction in disputes through education, engagement, and efficient escalation procedures.

Detected and reported fraudulent activities, strengthening compliance and platform security while enhancing customer trust within the seller ecosystem.

Core Competencies

Analytics Tools: SQL (MySQL), Python (pandas, numpy,), R, Statistical Analysis, Excel

Visualization Tools: Tableau, Power BI, Google Analytics

Soft Skills: Workflow Optimization, Reporting KPI Analysis, and Stakeholder Communication.

Projects

Gate City Bank – Fraud Detection & Spending Behavior Analysis Jan 2025 – Present

Developing a Python- and SQL-based fraud detection model to analyze suspicious transactions (e.g., multi-location spending anomalies). This system enhances financial security by proactively identifying high-risk activities, reducing fraud losses by an estimated 20%, and improving real-time risk assessment accuracy by 30%.

Built hierarchical clustering models (scipy, sklearn.cluster) to analyze ATM withdrawal trends and fast-food spending behavior, identifying high-risk spending clusters based on time, location, and transaction frequency.

Designed SQL-based transaction classification models using pivot tables and industry codes to categorize spending patterns across cities, addresses, and industries, distinguishing between in-store check-ins and online purchases.

Developing a location-based anomaly detection system (folium, geopandas) to track spending paths, identifying irregular movement patterns (e.g., McDonald’s purchase at 6 AM, another transaction miles away at 6:05 AM) to flag potential fraud.

Created a Tableau dashboard to visualize real-time transaction flows, mapping high-risk spending areas, ATM withdrawal patterns, and fast-food spending trends, enabling fraud analysts to take proactive action.

Integrating machine learning (IsolationForest, Local Outlier Factor, DBSCAN) to detect anomalous spending behavior, reducing false positives and improving fraud detection accuracy.

Automated SQL-based reporting workflows (PostgreSQL, SQLAlchemy), improving the fraud risk team’s efficiency by 30% through real-time alerts and structured reports.

Real-Time Motion Tracking & Data Analytics Project Sep 2024 – Present

Designed and implemented a real-time multi-camera tracking system using OpenCV, TensorFlow, and Python to capture human movement and golf ball trajectories.

Built a data pipeline to collect, clean, and store motion-tracking data, enabling speed, distance, and movement.

Developed a deep learning-based pose estimation framework, extracting human joint coordinates and ball movement data. Applied image processing techniques (HSV filtering, contour detection, and morphological transformations) to enhance object recognition accuracy.

Decentralized Autonomous Organizations (DAO) Research Jan 2024 – May 2024

Conducted research as part of the MIS 790 Blockchain Technology & Minting course, analyzing governance coalitions across 64 DAOs, tracking delegate voting power, proposal success rates, and token distribution.

Evaluated treasury management strategies for DAOs managing $25M+, identifying best practices in fund diversification, risk mitigation, and capital allocation to enhance financial sustainability.

Assessed the impact of governance on voter participation and decision-making efficiency, proposing optimizations to strengthen decentralized governance models.

Automated Stock Monitoring & Email Reporting with RPA Mar 2024

Developed an RPA bot to automate stock fluctuation tracking from Nasdaq.com, extracting real-time data and generating daily email reports to the professor for a week.

Implemented web scraping techniques using Python (BeautifulSoup, Selenium) to fetch stock price changes and structured insights into an automated email pipeline.

Enhanced efficiency in financial monitoring, reducing manual effort by automating stock data retrieval and reporting, showcasing practical applications of Robotic Process Automation in market analysis.

Event Participations

USC Big Data Health Science Case Competition – Participant 7th Feb – 9th Feb 2025

Built a predictive model for disease classification using Python, SQL, and Tableau, analyzing large-scale healthcare datasets (11.5 M+ Rows) to optimize treatment strategies.

Evaluated HIV treatment effectiveness, identifying key factors influencing viral suppression and CD4 recovery using statistical analysis and business intelligence methods.

Presented findings to industry leaders and healthcare professionals, showcasing expertise in data analytics, visualization, and decision-making frameworks.

Veterinary Care Market Analysis Using Power BI Aug 2024 - Sept 2024

Presented insights at the Veterinary Management Group Meeting (Jasper Hotel, Fargo, ND), providing recommendations to enhance veterinary service reach and efficiency.

Conducted data-driven analysis of ESRI reports to assess veterinary care accessibility, consumer spending, and pet ownership trends across multiple U.S. counties.

Built interactive Power BI dashboards to visualize market potential, community loyalty, and service accessibility scores, informing veterinary business strategies.

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