📧 Email: sm145@illinois.edu

A passionate data and business analytics professional, currently pursuing a Master of Science in Technology Management at Gies College of Business, UIUC. With a strong foundation in data science, machine learning, and business strategy, I thrive at the intersection of analytics, decision-making, and innovation.

I have hands-on experience in data visualization, predictive modeling, and consumer behavior research, leveraging AI and machine learning to drive business insights. As a Research Assistant, I am actively working on a research paper focused on consumer psychology and behavior, analyzing data-driven patterns to understand consumer decision-making.

My goal is to tackle complex business challenges by developing scalable, data-driven solutions while collaborating on real-world analytics and machine learning projects.

I enjoy solving complex business problems using data-driven approaches, leveraging AI, machine learning, and statistical analysis.

• Master of Science (MS) in Technology Management - University of Illinois Urbana-Champaign (Expected Aug 2025)
• Bachelor of Engineering (Mechanical) - Vellore Institute of Technology, India (July 2022)

• Data Analysis & Visualization: Excel, MySQL, PostgreSQL, Python, R, Tableau, Power BI
• Machine Learning & AI: Regression, K-Means Clustering, Classification, Time-Series Analysis, Random Forest, A/B Testing
• Cloud Platforms: AWS, GCP
• Method0logies: Agile Methodologies, Technical Documentation, JIRA, Scrum, SDLC, Waterfal
• Certifications: Google Advanced Data Analytics Professional, Six Sigma Green Belt (EY), AWS Cloud Practitioner (Ongoing)

• Assisted in enhancing conceptual models to visually represent key relationships in consumer behavior research, ensuring theoretical frameworks are clear and impactful.
• Refined statistical tables and data visualizations, making complex findings more intuitive and accessible for academic and industry audiences.
• Conducted literature reviews to explore emerging research ideas and identify potential directions for future studies.

• Designed an interactive dashboard using Tableau to visualize 250,000+ data points, increasing data transparency for 50+ stakeholders.
• Implemented ETL pipelines to integrate data from 5+ disparate sources, reducing inconsistencies by 15% and enhancing decision-making accuracy.
• Developed and optimized custom SQL queries, improving dashboard load performance by 35% and ensuring scalability for future data growth.
• Led project management initiatives by coordinating cross-functional teams, defining project roadmaps, and ensuring timely deliverables for data-driven education initiatives.

• Conducted quantitative risk-based analysis on 25,000+ active customers, optimizing financial crime detection and guiding managers in setting up 20+ CSPs (Customer Service Points) for SBI across India.
• Led the AML and trade surveillance initiative, successfully recovering $300,000 in fraud by shifting data reconciliation from monthly to daily, enhancing real-time risk detection.
• Developed predictive analytics models in Python to improve fraud detection by 40%, implementing above-the-line (ATL) and below-the-line (BTL) tuning for financial risk mitigation.
• Designed 50+ financial risk reports and trade surveillance dashboards, delivering 10+ high-stakes presentations to C-suite executives, improving compliance insights by 30%.
• Implemented risk assessment frameworks to evaluate transaction anomalies, reducing false positives in fraud detection models by 20%

• LinkedIn: LinkedIn
• Email: sm145@illinois.edu