MMA Candidate — McGill University
Bo-Jun "Esteban" Shen
Business Analytics · Data Engineering · Python · SQL · Machine Learning
Hands-on experience building Python/SQL data pipelines and machine learning models that hold up against millions of real records — now sharpening the statistics and ML side of the craft at McGill.
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I'm a business analytics professional pursuing a Master of Management in Analytics at McGill University, building on production data-engineering work and a business degree from National Taiwan University. I work at the point where raw, messy, high-volume data meets a decision someone actually has to make.
Pipeline built at Dun & Bradstreet Taiwan
2M+
patent records acquired and validated by an automated Python crawling and inspection system.
Independent classifier, NTU coursework
80%+
accuracy predicting stock direction from news data, after preprocessing 7.5GB independently.
Applied analytics across statistics, machine learning, automation, and visualization — in coursework and in production.
All projects ↓2
Machine learning & classification projects
1
Production data-engineering system, 2M+ records
1
SQL + Tableau visualization pipeline
6
Tools in active use — Python, SQL, Tableau, Power BI, Cognos, Excel
Selected work
Projects
Self-initiated
Formula 1 — McLaren Driver Pace Analysis
Applied design thinking to scope the core performance question facing the McLaren F1 team, then tested it statistically: ran t-tests on lap-pace data in Python and built visualizations comparing driver performance under varying race conditions.
PythonStatistical TestingData VizDesign Thinking
View on GitHub ↗
Big Data & Business Analysis — NTU
News-Driven Stock Price Classification
Independently built a classification model predicting stock price direction from news data, reaching over 80% accuracy while preprocessing a 7.5GB dataset — end to end, from raw text to evaluated model.
PythonClassificationBig Data Preprocessing
View on GitHub ↗
Data Analysis & ML with Python — NTU
Industry Impact on the Taiwan Weighted Index
Collaborated on machine learning models analyzing how Taiwan's largest industry sector influences movement in the Taiwan stock market's weighted index (TAIEX).
PythonMachine LearningTeam Project
View on GitHub ↗
Data Visualization & Modern Data Science — NTU
2024 Taiwan Election Dashboard
Visualized 2024 presidential and legislative election data in Tableau, with an automated pipeline connecting SQL to Python for scheduled data extraction.
TableauSQLPythonAutomation
How I work
Extract. Model. Decide.
STAGE 01
Extract
Pull and validate data at volume — Python crawlers, SQL pipelines, and automated inspection systems built to survive production limits, not just a notebook.
STAGE 02
Model
Test the hypothesis properly — statistical testing, classification, and machine learning applied to the actual question, not the easiest one to answer.
STAGE 03
Decide
Put results in front of someone who has to act on them — Tableau and Power BI dashboards built for a business decision, not just a chart.
Academic background
Education
Jul 2026 — exp. 2027
In progressMcGill University
Master of Management in Analytics (MMA)
Graduate program focused on statistics, machine learning, and applied analytics for business decision-making — building directly on prior work in data engineering and business analysis.
Sep 2020 — Jun 2025
National Taiwan University
Bachelor of Business Administration, International Business — GPA 3.54/4.3 (3.96/4.3, final 60 credits)
Relevant coursework: Marketing Research (statistics & visualization of relationship value across demographics); Data Analysis & Machine Learning with Python; Data Visualization & Modern Data Science (Tableau + SQL/Python); Big Data & Business Analysis (classification modeling on 7.5GB of news data).
Sep 2024 — Dec 2024
Queen's University — Smith School of Business
Exchange, Commerce — GPA 3.71/4.3
Business Decision Models (statistics, stock management, simulation in Excel); Coding Literacy for Managers (Excel, Power Apps, JavaScript, HTML); Knowledge Discovery & Research on time pressure and investor decision-making.
Professional history
Experience
Data Engineering Contractor
Dun & Bradstreet Taiwan
Feb 2025 — Nov 2025
- Built a Python web-crawling and auto-inspection system that acquired and validated over 2 million patent records without exceeding working-time compliance limits.
- Automated extraction, validation, and computation of annual-report data across 1,800+ companies (12 worksheets each) in partnership with a data-vendor team.
- Connected SQL and Python to validate Allianz Trade data, coordinating API integration with engineering partners.
- Shipped reusable Python automation modules that reduced manual processing time for the analyst team.
Intern
ROC-USA Business Council
Apr 2023 — Jul 2024
- Researched biotech policy and business environments in Maryland to brief delegation leadership.
- Presented findings directly to US delegates and senators; contributed to persuading 4 additional states to open Taiwan offices.
- Organized 4 expositions introducing US business investment opportunities.
Toolkit
Skills
Languages & Query
- Python
- SQL
- JavaScript / HTML
- Excel (advanced) / Power Apps
Analytics & ML
- Classification models
- Statistical testing (t-tests)
- Data engineering & ETL automation
- Big-data preprocessing
Visualization
- Tableau
- Power BI
- IBM Cognos Analytics
Certifications & Languages
- IBM Data Analyst Certificate
- English — IELTS 7.5
- French — DELF B1
Open to internships and full-time roles in business analytics and data science — reach out directly.