Personal Profile - Data Scientist

STEP BY STEP Data Scientist

I am a data scientist with a background that spans from business intelligence engineering to AI research. Over the years, I've worked on projects ranging from building BI solutions that support business decisions to exploring applications of artificial intelligence. This experience has helped me understand both the practical needs of businesses and the potential of emerging technologies, allowing me to contribute solutions that are useful, technically sound, and commercially relevant.

5+ Years Experience

15+ Business Projects

5+ Research Projects

8+ Industries Served

Skills & Expertise

Data Management

Database design, data warehousing, ETL pipelines, data governance and quality assurance

📊

Data Analysis & Visualization

SQL, Python, R for advanced statistical analysis. Power BI, MicroStrategy, Google Locker for interactive dashboards

⚙️

Programming & Automation

Python, C#, Java, automated workflows and ETL pipelines

💼

Business Intelligence

Transform data into actionable business insights and strategic decisions

🤖

AI & Machine Learning

TensorFlow, PyTorch, Scikit-learn, deep learning and NLP

☁️

Cloud Services & Container

Azure, GCP, Docker for scalable data solutions and ML deployment

Work Experience

Data Scientist (Freelancer)

Datas Co. Ltd.(Remote)

Jan. 2024 - Present

Designed and implemented machine learning-based sales forecasting models achieving 94% prediction accuracy. Developed and deployed scalable data engineering workflows using Google Cloud Platform, enhancing processing efficiency by 30% and improving analytics accuracy by 20%.

Data Scientist Intern

Quanmax AI (Remote)

Sep. 2024 - Dec. 2024

Streamlined metro system data management by designing scalable SQL solutions, boosting query response times by 30%. Leveraged Python, Pandas, and Numpy for large-scale transportation datasets analysis, achieving 20% decrease in commute delays through predictive machine learning models.

Research Assistant (Part-time)

Saint Louis University

Sep. 2023 - Feb. 2025

Developed GANs-based time series imputation model using Generative Adversarial Networks, achieving 91% accuracy in filling missing healthcare data. Performed data preprocessing and feature engineering using Python libraries (Pandas, Numpy, TensorFlow, PyTorch).

Business Intelligence Engineer

Mobile BI Technology Co., Ltd.

Mar. 2021 - Jun. 2023

Designed and managed data warehousing systems (MS SQL, MySQL, PostgreSQL, Oracle) across retail, manufacturing, food, and government sectors. Developed ETL processes to enhance data integration and streamline data transformation. Led predictive analytics projects using advanced statistical techniques and machine learning algorithms.

Academic Publications

International Journal

2025

Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data

Wen-Shan Liu, Tong Si, Aldas Kriauciunas, Marcus Snell , Haijun Gong

Stats, 8(1), 7

View Paper DOI Link

Abstract

This research presents a novel bidirectional f-divergence-based deep generative method for imputing missing values in time-series data. The approach leverages advanced deep learning techniques to handle complex temporal dependencies and provides robust solutions for incomplete time-series datasets, demonstrating superior performance compared to traditional imputation methods.

Data-Driven Professional