Data Analyst | Product Analytics | Business & Growth Analytics
I am a Data Analyst with hands-on experience in operational analytics, customer behavior analysis, and data-driven business problem-solving.
I enjoy turning raw data into actionable insights — from investigating operational bottlenecks and evaluating campaign performance to understanding customer behavior and building predictive models.
- Business & Product Analytics: Analyzed operational performance, driver behavior, campaign effectiveness, and customer engagement to identify growth opportunities.
- Data Analysis & Problem Solving: Experienced in SQL-based analysis, exploratory data analysis, root cause analysis, and translating findings into business recommendations.
- Customer Analytics & Machine Learning: Applied customer segmentation, churn prediction, and predictive modeling to support retention and customer risk analysis.
- Cross-functional Collaboration: Worked with operational and business stakeholders to investigate issues, communicate findings, and support data-informed decisions.
Business Analyst Intern — Ahamove | Analytics Team
- Analyzed driver behavior and operational performance using SQL and BigQuery, contributing to a 9% increase in driver utilization through auto-dispatch analysis.
- Conducted root cause analysis on declining short-distance driver acceptance rates and identified operational bottlenecks, with recommendations targeting a 7% AR improvement.
- Evaluated Dynamic Pricing impacts on driver productivity and service quality, supporting cross-functional business decisions.
- Built and maintained 5+ dashboards and automated reporting systems using Metabase and Looker Studio to improve operational KPI monitoring.
| Project | Focus | Technologies |
|---|---|---|
| ZaloPay – NPU Campaign Effectiveness | New paying user acquisition, campaign performance, subsidy efficiency, and business metrics | Python, SQL, Pandas |
| Customer Retention & Churn Prediction | Customer behavior analysis, churn risk profiling, and predictive modeling | Python, PySpark, LightGBM, SHAP |
| Retail Sales & Customer Segmentation | Customer segmentation, purchasing behavior, and discount effectiveness | Python, K-Means, PCA, Power BI |
| Price-Aware Fashion Recommendation | Personalized recommendation systems and model evaluation | Python, LightGCN |
Languages & Data Processing
- SQL, Python, Pandas, NumPy, PySpark
Analytics & Visualization
- Power BI, Metabase, Looker Studio, Google Sheets
Machine Learning
- Scikit-learn, LightGBM, XGBoost, SHAP
- Customer Segmentation, Churn Prediction, Recommendation Systems
Data & Analytical Methods
- Exploratory Data Analysis (EDA)
- Root Cause Analysis
- Cohort & Customer Behavior Analysis
- KPI Design & Performance Monitoring
- Statistical Analysis & Hypothesis Testing
International University – VNU HCMC
Bachelor's Program in Data Science
- IELTS 7.0
- HSK 4
Interested in product analytics, fintech, customer intelligence, and data-driven growth.