Data Analyst Power Bi

Trương Thuận Kiệt

********@***.*****.***.** • 077******* • https://www.linkedin.com/in/kiet-truong-thuan/ CAREER OBJECTIVE

Detail-oriented Data Analyst enthusiast seeking an internship to apply SQL, Python, and data visualization skills to analyze datasets, create impactful reports, and develop storytelling abilities under expert guidance. Committed to contributing to organizational goals and growing within the company. Long-term, I aim to master machine learning and deep learning to build predictive models, lead data-driven projects, and mentor future data professionals. TECHNICAL SKILLS

Data Visualization and BI: PowerBI, Tableau, Matplotlib, Seaborn, Pandas, NumPy, Notebook,PowerPoint, RStudio, Excel. Experimental Design: Hypothesis testing (ANOVA, Chi-square), A/B testing. Big Data Framework: Spark, Hadoop.

Programming Languages: Python, SQL.

Collaboration: Git/Github, VSCode.

WORK EXPERIENCE

HSBC - Data Analytics Office Intern July. 2025 - Present

● Designed and developed interactive dashboards in Power BI and Excel to track interdepartmental charges, enhancing transparency and streamlining financial reporting.

● Built and evaluated time series forecasting models using Random Forest, XGBoost, and Auto ARIMA to predict key financial metrics, supporting more accurate budget planning and resource allocation.

● Conducted and facilitated Power BI training sessions for cross-functional teams, improving their data literacy and empowering them to create self-service reports.

● Analyzed investment trends in the Vietnamese stock market (e.g., VNINDEX, VN30, VN50) using Ordinary Least Squares Regression and bootstrapping techniques, and backtested hypotheses to identify optimal investment strategies.

● Partnered with the Performance department to document and streamline the POA (Power of Attorney) control workflow for department managers, improving process clarity and handoffs. PROJECTS

Electronic Exports Sep. 2025

● Technologies used: Power BI

● Collected and analyzed 10 years (2013–2023) of Vietnam’s electronic trade data from the WITS database using HS-4 digit commodity codes.

● Processed export–import records by country and product type, identifying telecommunication equipment (HS 8517) as the dominant export, accounting for 93% of total export value (~$572B).

● Identified the United States, China, and South Korea as Vietnam’s top electronic trade partners, with export value to the U.S. reaching $118B.

● Developed a dashboard to visualize trends in export and import values by year, product category, and partner country.

● Provided strategic insights on potential growth markets (India, ASEAN) and underutilized import categories (e.g., cooling equipment).

● Github: https://github.com/truongthuankiet1990gmailcom/Electronic-Export Spotify Analysis (Position: Leader) April. 2025

● Technologies used: Jupyter Notebook, Power BI

● Collected and analyzed data on 4,735 songs and 1,409 artists from Spotify API and KWORB.

● Identified V-pop as the dominant genre with over 19.8 billion streams, accounting for the majority of Vietnam's Spotify activity.

● Determined Sơn Tùng M-TP as the leading artist with 865 million total streams and 6.5 million followers. Developed a Power BI dashboard with interactive filtering by year, genre, popularity, and artist, and visualized trends across genres and time.

● Integrated an AI chatbot via AI Lens to answer user queries using natural language.

● Github: https://github.com/truongthuankiet1990gmailcom/Intro-to-DV-Final Movie Data (Position: Leader)Dec. 2024

● Technologies used: Python, Jupyter Notebook, BeautifulSoup, Matplotlib, Seaborn, Scikit-learn

● Scraped and aggregated metadata for 3,500+ films from Rotten Tomatoes, Metacritic, The Numbers, and Investopedia.

● Visualized key trends and relationships such as genre vs. revenue and critic scores vs. box offices.

● Imputed efficiently 12% of missing budget and revenue entries with a hybrid approach: Random Forest regression and content-based similarity matching.

● Conducted feature selection via one-way ANOVA and Chi-square dependency tests to isolate the most impactful predictors.

● Developed and compared ensemble regression models (Random Forest, XGBoost, Gradient Boosting, Decision Tree), achieving 63% accuracy in categorical revenue brackets.

● Tuned hyperparameters with GridSearchCV, yielding a further 3% uplift in predictive performance.

● Github: https://github.com/truongthuankiet1990gmailcom/Intro2DS---HCMUS---2024 Stroke Prediction (Position: Leader)Dec. 2024

● Technologies used: Python, Jupyter Notebook, Pandas, Scikit-learn, XGBoost, Random Forest, Decision Tree

● Analyzed clinical data of 5,110 patients, identifying age, hypertension, and heart disease as top risk factors through feature-importance scoring.

● Imputed missing BMI values using Decision Tree regression, improving dataset completeness by 18% .

● Developed XGBoost and ensemble models to classify stroke risk, reaching 89% accuracy on held-out validation.

● Conducted hyperparameter optimization with GridSearchCV, enhancing precision and recall by up to 6%.

● Github: https://github.com/truongthuankiet1990gmailcom/StrokePrediction EDUCATION

University of Science (HCMUS) March 2025

Final year in Data Science GPA: 3.8

Relevant Courses: Machine Learning, Statistics, Data Science, Data Mining, Data Visualization, Big Data, Graph Mining ACHIEVEMENT

● 2nd Prize – City-level English Excellent Student Competition Awarded by the Ho Chi Minh City Department of Education for outstanding performance in English among top-performing high school students.

● 1st Rank out of 28 – Machine Learning Final Project (FIT@HCMUS) Achieved top performance in the university’s official Introduction to Machine Learning course project using regression models.

● Top 95 out of 266 Teams – Real Estate Demand Prediction (Kaggle) Developed and optimized machine learning models to forecast housing demand in China’s first real estate prediction challenge.

● Top 224 out of 1,298 Teams – Predicting the Beats-per-Minute of Songs (Kaggle Playground S5E9) Built regression models to estimate BPM from music metadata and audio features.

● Top 645 out of 4,381 Teams – Binary Prediction with a Rainfall Dataset (Kaggle Playground S5E3) Participated in a large-scale binary classification competition predicting rainfall occurrence. CERTIFICATION

SQL Intermediate - Hackerrank

IBM Machine Learning - Coursera

Google Data Analytics - Google

AI Ambassador - HSBC

SOFT SKILLS

● Collaboration: Worked effectively in team projects.

● Verbal and Written Communication: Delivered presentations and reports.

● Leadership: Guided peers in academic settings and in school projects.

● Patience: Supported diverse learning paces as a tutor. LANGUAGES

● English: IELTS Certificate 7.5

● Chinese: Be able to communicate at a basic level with foreigners.

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