Aryan Cheetewar

Analytically driven and results-oriented graduate with a Master’s in Information Systems & Technology, passionate about leveraging data-driven insights for strategic decision-making. Experienced in real-time fraud detection, machine learning, and business analytics projects. Skilled in SQL, Python, Tableau, and stakeholder collaboration, with a proven ability to drive operational improvements and contribute to business outcomes. Seeking to apply analytical and strategic thinking to solve high-impact business problems in a fast-paced, data-centric environment.

• Developed a real-time anomaly detection system using machine learning to identify suspicious transactions and reduce credit risk.
• Built dashboards to monitor transaction metadata, improving early detection of fraud patterns.
• Collaborated with academic mentors and presented strategic insights, simulating stakeholder analysis and reporting.

• Developed a real-time analytics platform to detect and mitigate fraudulent financial transactions, contributing to proactive credit risk management.
• Implemented anomaly detection algorithms using Python and machine learning to identify suspicious patterns, increasing fraud detection accuracy by over 25%.
• Designed and maintained interactive dashboards to monitor data quality and transaction metadata in real time, improving transparency and responsiveness.
• Led feature scoping and requirements analysis sessions to align system capabilities with fraud and compliance goals, simulating regulatory partnership.
• Presented model outcomes and risk trends to academic advisors, simulating executive-level stakeholder reporting.
• Integrated Azure ML models and enforced audit trails and metadata lineage for data governance and traceability.

• Engineered a self-service analytics platform using Python, Java, and MySQL to automate reporting for user engagement and conversion tracking.
• Collaborated with cross-functional stakeholders to define KPIs and translate business requirements into scalable analytical features.
• Delivered strategic insights to mentors through real-time visualizations, simulating communication with product and marketing teams.
• Applied data prioritization and ROI analysis to feature development, reflecting strong business judgment and decision-making under uncertainty.

• Designed and deployed a machine learning web application using Python and Flask to perform real-time image classification with 85% accuracy.
• Applied data preprocessing, augmentation, and performance tuning to optimize predictive performance and system usability.
• Practiced end-user centric design and reporting, reinforcing stakeholder-aligned outcomes and model interpretability.

• Designed and deployed a responsive web portal using HTML, CSS, and JavaScript to showcase projects and track engagement behavior.
• Integrated analytics tools and custom scripts for user interaction tracking, applying lightweight metadata tagging and behavior analysis.
• Deployed site using GitHub Pages and Netlify, ensuring reliable performance, accessibility, and continuous integration for iterative improvements.
• Practiced version control and stakeholder reporting by aligning site evolution with audience interaction insights, simulating product and marketing feedback loops.

• Infosys Certified Software Programmer.
• Offered roles as Programmer Analyst Trainee at Cognizant Technology Solutions.