Data Analysis Visualization

Lưu Quang Bảo

+84-889-***-*** **********@*****.*** Year of birth: 1998 Ward 15, Tan Binh Dist, HCMC

OBJECTIVE

I am passionate about using data-driven insights to make informed decisions and reducing reliance on subjective opinions. Through active investment in my professional development, I have acquired skills in descriptive and exploratory analytics. I am familiar with using data visualization tools like Power BI and querying data with SQL, and I aim to primarily focus on analysis and work with big data. Additionally, I have completed personal projects involving predictive analysis using machine learning models. PERSONAL PROJECTS

Visualizing and Analyzing Business Situation and Customer Satisfaction Metrics [LINK] Description: An e-commerce business in Brazil that has been operating for nearly 2 years wishes to analyze its business situation over the past 2 years to develop a business strategy for the upcoming period. Duties: Data Retrieval and Connection; Data Transformation and Cleaning; Data Modeling; Data Visualization, Report and Analytics.

Tools: My SQL; Power BI (Power Query, DAX).

Result: The report identified the strengths and weaknesses in the business situation over the past nearly 2 years in terms of revenue, delivery operations, and payment methods, thereby providing suggestions for the company's business strategy in the upcoming period.

Vehicle Loan Default Prediction [LINK]

Description: A financial institution offering car loans in India wishes to develop a machine learning model based on customer loan data from the past to predict the likelihood of customer defaults in the future, thereby enhancing the company's risk management capabilities.

Duties: Data Retrieval and Connection; Data Transformation and Cleaning; Data Exploration Analysis; Model Training; Model Evaluation; Presentation.

Tool: Google Colab – Python (Pandas, Numpy, Scikit-learn, Matplotlib). Result: Four machine learning models were used for experimentation, including Logistic Regression, Random Forest, Gradient Boosting, and K-nearest Neighbors. Among them, three models - Logistic Regression, Random Forest, and Gradient Boosting - achieved the best prediction results for customer default on the test set with an Accuracy and F1-Score of 100%. The KNN model achieved 75%.

SKILLS

Programming languages: SQL, Python (pandas, numpy, matplotlib, seaborn, and scikit-learn) Data Analysis skills: Data cleaning; Exploratory Data Analysis; Data Visualization Tools: MS Excel, Power BI, Oracle SQL, MySQL, Visual Studio Code, Google Colab Language: English (TOEIC 795)

WORK EXPERIENCE

03/2022 – 06/2024 Samsung Electronics HCMC CE Complex Logistics Warehouse Operations

• Utilized MS Excel and WMS to manage daily operations for approximately 50,000 televisions, incorporating the scanning of goods.

• Generated daily reports for the Manager regarding the status of finished goods, including information on issues, volume of defective goods, and rework plans.

• Followed up on daily operations and production plans, tracking issues and the volume of defective goods.

• Collaborated with the Production, QC, and R&D departments to ensure timely resolution of issues, facilitating the packing and shipping of finished goods before the closing time.

• Utilized descriptive analysis to identify measures to improve team performance, and proposed solutions in collaboration with relevant departments to enhance delivery efficiency and avoid inventory backlog in the factory.

• Ensured 100% of products were accounted for and no defective containers left the factory. EDUCATION

2023 MindX Technology School

Data Analysis course

2018 – 2021 Ho Chi Minh City College of Economics

Associate degree in Logistics

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