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Data Analyst with less than a year in Salesforce & Front End Development
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Highly motivated Computer Science and Engineering student specializing in Business Systems with a strong foundation in Python, SQL, and data analysis tools. Possessing practical experience in Salesforce administration, front-end development, and machine learning projects focusing on predictive maintenance, financial performance tracking, and fraud detection. Eager to leverage analytical skills and technical expertise to drive operational efficiency and informed decision-making.
Vellore Institute of Technology
B.Tech · Computer Science and Engineering with Business Systems
August 1, 2020 – June 30, 2024
AVATAR
Front End Developer Intern
May 1, 2023 – July 1, 2023
India
Salesforce
Salesforce Administrator
May 1, 2023 – August 1, 2023
India
Building Management System and Predictive Maintenance
June 21, 2026 – Present
• Developed comprehensive data models and automated data processes, increasing operational efficiency by 30% and improving resource utilization by 25%. • Led development of comprehensive BMS, optimizing operational efficiency by 30% and resource utilization by 25%. • Analyzed large datasets to identify performance trends and generate actionable insights for maintenance and operations.
Machine Learning-Based Transaction Fraud Identification
June 21, 2026 – Present
• Built ML models detecting fraudulent transactions with 0.9845 AUC, reducing false positives by 84% vs. baseline. • Performed exploratory data analysis (EDA) on 200k+ transactions, identifying critical fraud indicators: fraud rate peaks at 0.8% during high-risk hours and legitimate transactions dominate (99.83%) • Designed interactive Power BI dashboard visualizing fraud trends, feature correlations, and model performance, enabling data-driven decisions for fraud strategy adjustments.
Financial Performance Tracker for Credit Cards
June 21, 2026 – Present
• Built a Power BI dashboard for analyzing credit card financial data, integrating PostgreSQL for data storage. • Analyzed key performance metrics, identifying a 28.8% increase in revenue and a 35.04% rise in total transaction volume for week-over-week analysis. • Created visualizations to track credit card revenue distribution, with 82.45% revenue contribution from Blue Credit Cards and a 54.38% share from male customers. • Generated actionable insights on activation rates (57.5%) and delinquency rates (6.06%), improving credit card management strategies.
Soccer Performance Analytics
June 21, 2026 – Present
• Built an end-to-end data pipeline to collect, clean, and analyze over 10,000 rows of soccer match data from multiple sources, improving data accessibility and reducing manual processing time by 40%. • Designed and deployed machine learning models (e.g., logistic regression, XGBoost) to predict soccer match outcomes, achieving an accuracy rate of 85% and providing actionable insights for team strategy optimization. • Developed Python scripts to automate data cleaning and preprocessing, reducing data errors by 25% and improving the reliability of analytical outputs for team performance analysis.
Cultural Fit Analysis
The candidate's academic projects cover diverse domains such as building management, finance, fraud detection, and sports analytics, indicating a broad interest and adaptability. The inclusion of 'Business Strategy' as a technology in one project and 'Business Systems' in their degree suggests an understanding of business context, which is valuable for cultural fit in a data-driven organization. However, the lack of professional data analyst experience means their fit within a corporate data team's specific workflows and collaborative dynamics is yet to be fully proven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, optimize processes, and deliver measurable results. The Salesforce Administrator internship suggests an aptitude for system customization and user support, which implies problem-solving and attention to detail. The Front End Developer internship, while not directly related to data analysis, shows versatility and an understanding of web technologies. The academic nature of most projects means real-world operational experience is limited, but the descriptions suggest a proactive and results-oriented approach.