🎓 BMath (Co-op) @ University of Waterloo
Applied Mathematics (Scientific Machine Learning) & Statistics
Computing Minor

📊 Data Science · Analytics · Applied Machine Learning
📈 AI · Growth · Product Strategy
📍 Waterloo, Canada

I’m a Mathematics student at the University of Waterloo with a strong interest in data science, analytics, and applied machine learning.
I enjoy working on real-world problems where data, AI, and strategy support business growth, product decisions, and scalable systems.

My focus is not just on building models, but on understanding why they work, how they perform in practice, and how insights are communicated clearly to both technical and non-technical stakeholders.

AI & Software Developer — Savi Finance

• Built backend services and AI-driven automation pipelines, reducing manual operational effort by 30%+
• Shipped production-facing features supporting 1.5k+ active users in an early-stage fintech startup
• Collaborated on modular architecture to improve system reliability and scalability

AI & Growth Strategy Intern — RipenLabs (EdVising AI)

• Supporting growth and product strategy through data analysis, market research, and AI-driven insights
• Analyzing user behavior, engagement metrics, and early adoption signals to inform go-to-market decisions
• Assisting with metric design, experimentation, and insight generation for an AI-powered education platform

Co-Founder — Wanderers

• Building a community platform focused on interest-based connections and real-world engagement
• Designing backend systems for user profiles, interest tagging, and matching logic to support scalable growth

Ownership Consulting Member At-Large - WUSA

• Contributed to committee decision-making that supported the introduction of Saturday GO Train service from Kitchener to Union Station, consulting with Members-at-Large to address student transportation barriers.

📌 ChurnLens — Customer Churn & Revenue Analytics Platform

• Built modular and optimized SQL pipelines to compute churn metrics, LTV, and revenue loss
• Designed BI dashboards using Power BI / Tableau to support retention strategy and business decisions

📌 Accident Severity Predictor — ML & Data Visualization System

• Developed end-to-end ML workflow including data ingestion, EDA, and feature engineering
• Applied K-Means clustering for pattern discovery and trained a supervised model achieving ~80% accuracy

📌 VectorMate — Neural-Network-Based Chess Engine (In Progress)

• Building a chess engine using neural-network-based evaluation with PyTorch
• Targeting an ELO rating of 1000+ through improved move selection and search strategies

Languages: Python · SQL · Go · Java · JavaScript · TypeScript · Racket
Data & ML: Pandas · NumPy · Scikit-learn · PyTorch · EDA · Feature Engineering
Visualization & BI: Power BI · Tableau · Matplotlib · Seaborn · Excel
Databases & Cloud: MySQL · MongoDB · BigQuery · AWS (Fundamentals) · GCP
Growth & Strategy: Metrics Design · Experimentation · User Analytics · Market Research