Work Experience#
Microsoft – Summer 2024#
Data & AI Technical Specialist Intern#
At Microsoft, I really enjoyed the opportunity to dive into some of the most challenging and high-impact projects I’ve worked on, combining both technical prowess and business strategy. I helped major financial, public, and retail sector clients move to Azure OpenAI solutions, demonstrating generative AI could be used to accelerate business operations. A huge win came when I helped one of the leading financial institutions onboard 16 teams onto Azure by coaching them to success at Canada’s largest banking GenAI hackathon—an effort that contributed to a significant increase in Azure consumption and new projects compared to competitors.
Note
I think the best way to sum up this role is “hackathons + case competitions as a job,” and I’m all for it.
I also played a significant role in prototyping “chat with your data” applications, providing clients with a seamless way to integrate Azure OpenAI’s retrieval-augmented generation (RAG) services. My work here extended beyond delivering functional demos—it meant becoming a trusted advisor and showing how embedding SQL into their architecture could evolve their data practices.
Alongside the client-facing work, I designed a tool that translates SQL stored procedures to Spark SQL for use in Azure Databricks. The goal was to make SQL-to-Spark migration faster while keeping things intuitive for internal architects and customers alike. With Jupyter Notebooks at the core, the tool broke down complex SQL workflows into easily manageable steps, allowing our clients to see dependencies clearly and optimize their code.
Impactful Outcomes#
Client Hackathons: Coached client teams through a GenAI hackathon, securing top three placements and driving executive endorsement to choose Azure as their LLM platform.
Custom Solutions: Delivered retrieval-augmented generation (RAG) applications for major financial and retail clients, showcasing the power of integrated cloud-native AI.
T-SQL to Spark Converter: Built and deployed a tool that cuts SQL-to-Spark migration time by 60 to 80 hours per client project, directly increasing Azure Databricks adoption.
Environment and Climate Change Canada (ECCC) – Fall 2023 & Winter 2024#
Data Scientist Intern#
During my third year of university, I worked 20 hours a week with the Canadian government to improve their national waste characterization reporting. I designed data pipelines to consolidate 200 sources into a unified data warehouse using Python and SQL, streamlining analysis that used to take weeks. I also created the department’s first chatbot, enabling analysts to search through thousands of PDF documents in seconds, saving them two hours per week on average. The success of this tool led to a formal demo for its replication across teams in the department.
I’ve made a demo publicly accessible here: https://deepblue-ai.vercel.app/.
Impactful Outcomes#
Chatbot Development: Built a search chatbot for business analysts, saving 2 hours/week per user.
Data Unification: Engineered a solution to combine 200 waste report sources, streamlining government reporting.
Ernst & Young (EY) - Summer 2023#
Technology Consultant Intern (Generative AI & Program Management)#
In my second summer at EY, I worked on cutting-edge projects centered around generative AI. Partnering closely with Microsoft, I helped lead the development of a generative AI risk framework. This framework tackled crucial regulatory and compliance concerns that our banking clients faced when adopting disruptive technologies like OpenAI. By conducting targeted research and prototyping information retrieval systems, we showed how generative AI could be used responsibly within highly-regulated environments.
I also continued working on new product development for calculation and process automation in the insurance sector, as well as data migration tasks for a core banking transformation. This included leading stand-ups and facilitating design sessions with a 10-person product team. I worked with my team to manage cybersecurity and UI/UX testing alongside development.
Toronto-Dominion Bank (TD) - Fall 2022#
Business Analyst Intern (Agile Transformation)#
At TD, I worked as a Business Analyst Intern focused on Agile transformation in the Next Evolution of Work initiative. My responsibilities included providing bi-weekly debriefs to senior executives, where I used Power BI to track the implementation of scaled Agile methodologies. I reported on Jira epics, roadmap progress, and blockers, helping the organization prioritize and manage risk effectively during their transformation process.
Ernst & Young (EY) - Summer 2022#
Technology Consultant Intern (Data Engineering)#
In my first summer at EY, I concentrated on data engineering projects for financial institutions. I developed a high-performance actuarial calculation engine, leveraging Python and Azure to produce IFRS 17 Premium Allocation Approach (PAA) statements at 4 times the speed of competitors, helping to bring in additional client work. Additionally, I worked with migrating retail customers across banking systems using Azure Data Factory and SQL as part of EY’s largest banking transformation project.
Through the use of the DeepL API, I reduced the localization costs for a credit union’s user interface significantly, completing the project in just less than a week compared to the typical month-long timeline of hiring professional translators.