ZHENG HUIYING / UPM

Hello everyone, my name is Huiying Zheng, and I am currently a Master’s candidate in Computer Science at Universiti Putra Malaysia (UPM), maintaining a strong GPA of 3.8/4.0.

My core competence lies in a robust data analytics tech stack and practical experience in machine learning. I am proficient in SQL for complex querying and optimization, and I skillfully utilize Python (Pandas, Scikit-learn) for data cleaning, preprocessing, and model development.

In my project experience, I didn't just apply classical methods like RFM and Funnel Analysis to gain user insights; more critically, I possess predictive modeling capabilities. I successfully utilized K-Means clustering for customer segmentation and built predictive models using XGBoost and Time Series Analysis to forecast business trends, ultimately achieving a prediction accuracy of over 70%.

I am highly motivated to translate my technical expertise into quantifiable business insights for your company and look forward to diving into real-world commercial challenges.

Data Operations and Analytics professional with hands-on experience in SQL, Python, Power BI, and the Hadoop ecosystem (HDFS, PySpark, Hive, Sqoop). Previously worked as a Data Operations Engineer at Huigu Technology, maintaining and optimizing the UFIDA Government Financial System. Skilled in ETL workflow design, process automation, and data-driven problem solving. Currently focusing on data analytics and machine learning applications, with proven ability to translate business requirements into analytical insights and operational improvements.

Master of Computer Science student at Universiti Putra Malaysia (UPM), specializing in Data Analytics and Big Data Engineering. Coursework and research emphasize Python-based data processing, machine learning, and distributed computing with Spark and Hive. Achieved CGPA 3.8 and developed applied projects in digital agriculture analytics and credit risk modeling, integrating statistical and business intelligence methods.