Harvey Zhu
Harvey Zhu
Learner
(1)
31
Portals

Skills

Artificial intelligence 2 Lead generation 2 Research 2

Achievements

Latest feedback

Recent projects

Work experience

Financial Analyst Intern
Ministry of Public and Business Service Delivery, Ontario Public Service
Toronto, Ontario, Canada
May 2024 - August 2024

• Led financial analysis and user research across 15 program areas, uncovering key financial trends that informed a strategic $20M+ fund reallocation; provided recommendations to optimize distribution based on patterns and program-specific needs
• Conducted user research and assessed program performance to design a restructuring initiative for the Ontario Public Service; implemented an optimized departmental structure that reduced operational costs by 12% to support a seamless transition
• Developed an onboarding presentation for the new Deputy Minister, synthesizing insights on the Ministry’s $2B financial landscape, including key objectives, strategic priorities, and financial status to facilitate informed decision-making

Data Analyst
Ivey Business School
London, Ontario, Canada
September 2023 - Current

• Processed and analyzed 3M+ US patents using statistical software (Python, SQL, R, Stata) to identify trends in innovation and patent filing patterns; presented visual findings to support data-driven decisions across product development and research teams
• Compiled a dataset of 3,500+ records on patent licensing to identify trends and anomalies through data cleaning and validation to ensure accuracy, and synthesized insights into a detailed report highlighting key metrics and patterns
• Developed trend analysis frameworks to assess 65+ years of patent innovation across various Fortune 500 companies (e.g., Apple, Meta, Google, HP), uncovering insights that supported product roadmap planning and cross-functional collaboration

Project Manager Intern
Zengco Sign and Construction
Toronto, Ontario, Canada
May 2023 - August 2023

• Introduced Agile methodologies (Jira, Confluence) and facilitated Agile sprints, reducing time spent on the original project roadmap and improved execution speed by 10%, contributing to an improved 4.95/5 user satisfaction rating across all projects
• Led 100+ client meetings to resolve customer concerns and gather feedback by identifying recurring questions and pain points to enhance product features, resulting in 15 net new client contracts worth $750,000
• Managed a $100,000 budget, identifying spending trends and securing a $10,000 in cost reduction through strategic vendor negotiation, reinvesting savings into quality improvements that enhanced product features and client satisfaction

Education

Computer Science and Honours Business Administration Dual Degree, HBSc & HBA
Ivey Business School, Western University
September 2022 - April 2027

Personal projects

LinkedIn Search AI
https://docs.google.com/presentation/d/1qFu_yBUJm1QpVrruFhhm8NmAFXJIehvYyy27Ivo0oYs/edit?usp=sharing

• Prototyped LinkedIn Search AI, an AI-powered feature designed to streamline career exploration and mentorship discovery, by conducting user analysis and developing a high-fidelity mockup using Figma
• Conducted user experience research through 10+ user interviews, summarizing key pain points and testing prototype iterations

INFU: I’ll Never Forget You
November 2023 - November 2023
https://devpost.com/software/infu

• Awarded 2nd place and best use of Google Cloud; a tool to recall names and past interactions in social and professional settings
• Built a backend pipeline using Google Speech-to-Text, OpenAI APIs, and Firebase to process facial data and conversations
• Designed a wearable attachment with an ESP-32, OLED display, and wired touch controls for real-time face recognition and conversation summaries using OpenCV and the Python Face Recognition Library

DataQuest: The Science & Art of Preventing Booking Cancellations
March 2023 - March 2023
https://devpost.com/software/the-best-solution

• Awarded 1st place ($1,000); a machine-learning classification model to predict hotel cancellations based on a provided dataset
• Conducted Exploratory Data Analysis and feature engineering, leveraging cross-validation techniques to identify key predictors
• Trained and evaluated six machine learning models, selecting Random Forest for the highest predictive accuracy, achieving a 91% accuracy and 93.4% F1 score on the final test data