Data Analyst Entry

Chau Thanh Uy

*** ****** *, **** **, Go Vap, HCM, Viet Nam *******************@*****.*** 089******* Facebook Github linkedin

About me

Passionate about data and technology, I thrive on solving problems, uncovering insights, and turning data into impactful decisions. I value collaboration and communication as key to driving results, and I see every challenge as a chance to grow. With curiosity and determination, I’m committed to bridging any knowledge gaps and contributing meaningfully in data-driven environments. . Consistency - Discipline - Creativity

Education

University of Economics and Law, Bachelor in Economics Mathematics Sept 2021 – May 2025

• GPA: 3.1/4.0 (link)

• Coursework: Advanced Mathematics, Financial and Monetary Theory, Data Analysis, Financial Mathematics, Skills summary

Languages: MySQL, Python,

Frameworks: Pandas, Numpy, Scikit-Learn, Matplotlib Tools: PyCharm, Azure Data Studio, Visual Studio Code, Excel, Stata, SPSS, Tableau Soft Skills: Communication, Teamwork, Analytical Thinking, Problem-solving, Creativity, Self - Learning, Adaptability, Data Storytelling, Data-driven decision Experience

Data Analyst Intern, PiHome, HCM Dec 2024 – March 2025

• Processed and managed data entry for apartments and residents, ensuring accurate and organized datasets.

• Visualized key data insights to aid decision-making for clients and stakeholders.

• Analyzed operational data to optimize business processes and enhance customer satisfaction.

• Collaborated with cross-functional teams to implement data-driven solutions for effective property management. Awards

National Econometric Award, Consolation Prize, Vietnam (link) May 2024 Scientific research in the field of information technology, Consolation Prize, UEL, HCM (link)

Feb 2024

Projects

SALES PREDICTION project

• Build a linear regression model to predict sales based on advertising budget.

• Explored the dataset and visualized the relationship between advertising budget and sales.

• Insights: TV advertising plays a key role in driving sales, with increased investment in TV ads strongly linked to higher revenue. The strength of this relationship suggests that marketing efforts on TV are highly effective and should be prioritized in the media mix. This highlights the importance of strategically allocating a budget to maximize return on advertising spending.

• Tools Used: Python, Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn INTEGRATING MACHINE LEARNING MODELS INTO CREDIT ASSESSMENT project

• Implemented multiple models for credit assessment; Random Forest and XGBoost achieved the highest accuracy.

• Impact of Digital Footprints: Identified key factors such as DF_Internet Access, DF_E-Invoice, and DF_Shopping Online as highly influential in credit evaluation.

• Insights: Customers with frequent Internet access demonstrate better access to financial services, reflecting a high level of digital connectivity. The use of electronic invoices indicates transparent and organized financial behavior. In addition, frequent online shopping suggests high consumer activity and active participation in the digital economy.

• Research Findings: Integrating digital footprints improved prediction accuracy by 7 - 12% compared to traditional models.

• Practical Application: Provided a more effective credit scoring method for banks and financial institutions.

• Tools Used: Python, Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn CLEAN DATA LAYOFFS project

• Description:

Cleaned and standardized a real-world layoff dataset using SQL, simulating a common data preprocessing workflow in analytics projects.

• Key tasks:

– Created a staging table to protect raw data integrity.

– Identified and removed duplicate records using ROW_NUMBER and Common Table Expressions (CTEs).

– Standardized text fields (e.g., trimmed whitespaces, unified categorical values).

– Converted date formats from text to DATE type.

– Handled null or blank values using conditional joins and deletions.

– Dropped helper columns post-cleaning to finalize the dataset.

• Tool: MySQL Skills: Data Cleaning, CTEs, Window Functions, Data Standardization

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