Che Zhu

Data Analyst & Cloud Engineer

Hi, I'm Che Zhu.

I build cloud-native pipelines, automation frameworks, and AI solutions that transform how organizations leverage their data.

Get in touch View my work
3+
Years of experience
8M+
Records analyzed
3.91
GPA — UofT MI
Sun Life
Current role

About

Beyond the data.

I'm a Data Analyst at Sun Life Global Investments, where I architect cloud-native data pipelines, build automation frameworks, and develop AI solutions that transform how the business leverages its data.

My journey started in Environmental Physics at the University of Toronto — studying the patterns of our natural world. That curiosity for uncovering hidden structures led me to a Master's in Human-Centered Data Science, bridging the gap between complex models and real human impact.

Outside of work, I find calm in nature and thrill in discovery. Whether it's hiking trails around Ontario, experimenting with new recipes, or exploring the latest in generative AI — the best ideas come when you step away from the screen.

Cloud Engineering
Azure, AWS, Snowflake — building scalable data infrastructure
Automation & ETL
End-to-end pipelines that run reliably at scale
AI Solutions
From LLMs to predictive models — practical AI for business
Data Analytics
Turning millions of records into actionable insight

Life Outside Work

Built different.

When I'm not engineering data pipelines, you'll find me engineering something else entirely.

Car Enthusiast

Car enthusiast at heart.

There's something about the precision of a well-tuned machine that resonates with me — both on the road and in code. I'm passionate about the automotive world, from the engineering under the hood to the design language on the surface. It's the same attention to detail I bring to every data pipeline and model I build.

Weekends are for scenic drives, weekend wrenching, and the occasional track day. The philosophy carries over: build it right, make it fast, keep it clean.

Skills

Technologies I work with.

Data & Analytics
PythonR SQLSAS PandasNumPy Scikit-learnPower BI TableauExcel / VBA
Cloud & Infrastructure
Microsoft AzureAWS SnowflakeSnowpark DatabricksOracle ETL / ELTCI/CD Git
Machine Learning & AI
LLMsTensorFlow PyTorchXGBoost NLPNeural Networks Time SeriesClustering Classification
Databases & Languages
MySQLDB2 JavaC ArcGISMatplotlib ggplot2

Experience

Where I've made impact.

Data Analyst Current
2024 — Present
Sun Life Global Investments
  • Architect and maintain cloud-native data pipelines on Azure, enabling reliable and scalable data flow across investment analytics platforms.
  • Design and implement end-to-end ETL/ELT workflows and automation frameworks that reduce manual processes and accelerate data delivery to stakeholders.
  • Develop and deploy AI-powered solutions — including LLM-based tools and predictive models — to enhance decision-making across investment operations.
  • Collaborate with cross-functional teams to translate business requirements into robust data engineering solutions, driving efficiency in global investment reporting.
AzureSnowflakePythonETLCI/CDLLMsDatabricks
Data Analyst
May 2023 — Dec 2023
Royal Bank of Canada — Insurance
  • Led end-to-end migration and redevelopment of a predictive model for Future Income Options using LightGBM and XGBoost, boosting retention forecasting accuracy to 91.6% and contributing $1.13M in incremental sales revenue.
  • Engineered a novel Customer Loyalty Score metric that significantly improved model predictive power and operational efficiency.
  • Conducted multi-granular customer behavior analysis across 8M+ records spanning 40 years using DB2 SQL and Python, driving downstream segmentation and strategy initiatives.
  • Presented data-driven insights to cross-functional stakeholders across Data Engineering, Product, Risk, and Marketing teams.
PythonDB2 SQLXGBoostLightGBMPredictive Modeling
Economic Data Research Assistant
Sep 2021 — Apr 2022
University of Toronto
  • Collaborated on education policy research, mining data from government reports and institutional assessments using Python web scraping and Excel.
  • Delivered structured datasets and analysis contributing to published research on Ontario education system disparities.
PythonWeb ScrapingExcelData Mining

Projects

Selected work.

Retention Forecasting Model
Built and deployed a LightGBM/XGBoost predictive model for insurance retention at RBC. Introduced a novel Customer Loyalty Score feature.
91.6% accuracy — $1.13M incremental revenue
PythonXGBoostLightGBMSQL
Cloud Data Pipeline Architecture
Designed scalable ETL/ELT pipelines on Azure and Snowflake at Sun Life, automating data ingestion and transformation for investment analytics.
Reduced manual processing, enabled near-real-time access
AzureSnowflakeDatabricksCI/CD
Racial Disparity Analysis — TPS
Statistical analysis of racial disparities in strip search rates using 65K+ Toronto Police records with controlled confounding factors.
89.67% model accuracy — ANOVA, ANCOVA, Logistic Regression
PythonStatisticsLogistic Regression
Fraud Detection — Hackathon Finalist
Finalist in the 2023 UofT Faculty Hackathon, building a fraudulent activity detection system for Service Canada Family Benefit claims.
2023 Faculty Hackathon Finalist
ML ClassificationPythonData Science

Education

Academic foundation.

Master of Information
University of Toronto
Graduated Jun 2024
  • Concentration in Human-Centered Data Science
  • cGPA: 3.91 / 4.0
  • Coursework: ML, MLOps, Data Analytics, Practical AI Dev
  • Hackathon Finalist — Fraud Detection
Honours Bachelor of Science
University of Toronto
Graduated Jun 2022
  • Specialist in Environmental Physics
  • Dean's List (2019 — 2022)
  • Coursework: ArcGIS, Software Design, Statistics
IBM Data Science Professional
Databricks Generative AI
PwC Excel Problem Solving
SAS Programming

Contact

Let's work together.

Open to opportunities in data engineering, cloud architecture, and AI.

@
Email
Chezhu064@gmail.com
T
Phone
437-984-0704
in
LinkedIn
Che Zhu
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GitHub
Ohio-Tea