# Linsi Zhong

> Data & business analyst and University of Waterloo Math/Statistics grad, actively looking for DA/BA roles. Builds data pipelines, runs A/B tests, and ships dashboards - from churn prediction to ad-spend optimization.

Actively looking for Data/Business Analyst roles. I turn multi-gigabyte datasets into decisions - SQL pipelines, statistical testing, and dashboards stakeholders actually use.

## Contact

- Email: linsi6280@gmail.com
- Site: https://linsizhong.com
- LinkedIn: https://www.linkedin.com/in/linsizhong/
- GitHub: https://github.com/linsi6280

## Machine-readable

- [Résumé, JSON Resume schema](https://linsizhong.com/api/resume.json)
- [Résumé, PDF](https://linsizhong.com/downloads/Resume.pdf)
- [OpenAPI description of this site](https://linsizhong.com/api/openapi.json)
- [MCP server](https://linsizhong.com/mcp) - Streamable HTTP. Tools: get_profile, list_projects,
  get_experience, search, get_resume. No authentication required.

## Current role

Bank of Communications - Business Analyst Intern (May 2024 - Aug 2024)

- Automated data extraction and preprocessing for multi-gigabyte customer datasets using SQL queries, reducing manual data preparation time for weekly business reports.
- Developed key features and preprocessed data using Python (pandas, NumPy) for a customer churn prediction model, boosting predictive accuracy by 16% and identifying 10 primary churn indicators.
- Designed and deployed Tableau dashboards to track KPIs such as customer acquisition cost and product penetration, equipping the retail banking team with actionable insights for strategic planning.

## Selected work

- **Marketing Campaign A/B Testing Analysis** (Independent Project) - Ran an A/B test on 588K users to quantify the effect of ad exposure on conversion with a two-proportion z-test in Python, finding a statistically significant 43% relative lift in conversion rate (p < 0.0001). Validated the effect via logistic regression controlling for total ad exposure, day, and hour, then recreated the workflow in SQL with a Tableau dashboard visualizing conversion trends by day and hour. [SQL, Python, Tableau, Logistic Regression]
- **NovaMart Marketing Analytics** (Independent Project) - Built an end-to-end data pipeline with data cleaning and sentiment analysis on customer reviews. Delivered an interactive Power BI dashboard visualizing KPIs and data-driven recommendations to shift ad spend toward higher-performing channels, improving customer satisfaction. [SQL, Python, Power BI]
- **Implementing and Comparing Optimal Survival Tree Algorithm** (Independent Project) - Cleaned an R-package dataset, built a life table, and constructed three survival models (Cox, RSF, OST) in R - identifying Cox as the top performer and OST as optimal relative to RSF based on Concordance and AUC. Achieved 82% final prediction accuracy by applying tree pruning to mitigate model overfitting. [R, Survival Analysis, Cox, RSF, OST]
- **Course Schedule Optimization** (Independent Project) - Built and solved a linear programming model in Python with Gurobi to optimize course-schedule assignments under real-world constraints, increasing professor satisfaction scores by 34%. [Python, Gurobi, Linear Programming]

## Stack

Python, R, SQL, SAS, Matlab, MySQL, Snowflake, AWS, R Studio, Excel, Power BI, Tableau, NumPy, pandas, Matplotlib, SciPy

## Education

University of Waterloo - Bachelor of Mathematics, Mathematical Studies (Honours), Statistics Minor, President's Scholarship (2020-09 to 2024-10)