Toronto, Ontario, Canada
I’m a Computer Science student with an AI specialization at the University of Waterloo and a Business Administration student at Wilfrid Laurier University, with experience spanning software engineering, cloud automation, testing, and technical project management. I’ve worked across startups, enterprise teams, and public sector environments, building AI-powered features, internal platforms, and scalable systems that improve reliability, efficiency, and user experience. I’m especially interested in solving complex problems, learning quickly, and building technology that creates real-world impact.
- Enhanced the Customer Data Platform Segment Builder by adding new customer attributes, advanced comparison operators, and validation improvements, enabling more expressive, reliable, and scalable audience segmentation. - Built an AI-powered natural language segmentation engine that converts user intent (e.g., “Users in Boston”) into structured segment criteria, leveraging a Python-based MCP server for NLP inference and orchestration. - Designed and implemented a Segment Insights Dashboard surfacing actionable engagement metrics (e.g., open rates, customer activity levels), empowering marketers to evaluate segment quality and optimize campaign performance. - Developed AI-driven automation workflows using n8n to analyze and evaluate customer service calls recorded via Gong, streamlining review processes and delivering scalable insights for internal teams.
- Developed automated SAS Viya and AWS Lambda/Python procedures for efficient archiving and restoring of data to AWS S3, improving overall data management workflows. - Executed controlled penetration testing by deploying JAR (Java Archive) probes to trigger system callbacks, identifying data exposure risks on SAS Viya per NIST standards. - Tested over 100 complex SAS Visual Analytics reports on AWS Cloud, identifying issues and recommending improvements.
- Developed a scalable framework for front-end development on Retool platform, reducing project setup time by half. - Configured a Playwright testing platform, boosting test coverage and minimizing post-deployment bugs by 25%. - Designed reusable UI components and templates as modules to ensure consistency and efficiency across applications. - Implemented API integrations, enabling real-time access to essential business data and streamlining manual processes. - Resolved a critical production blocker by identifying and fixing a core performance bottleneck, preventing fallback to a less efficient workaround and enabling stable deployment.
- Collaborated with cross-functional teams to implement Salesforce Sales and Service Cloud solutions. - Utilized Selenium WebDriver and Apex Test Classes to create automated test scripts, achieving near 100% testing accuracy. - Ensured seamless system integration for 100K+ records by validating data integrity and performing data migration testing, - Conducted regression/sanity testing and monitored system performance, ensuring stability across Salesforce releases.
- Led and executed all project phases to build a Machine Learning model, predicting device disruptions for wealth advisors over 1 hour in advance, achieving 80% accuracy. - Applied advanced data analysis techniques using the Splunk ML toolkit to build a high-precision model. - Utilized data from Postman APIs to enhance model performance, boost prediction accuracy, and increase system reliability.