🎓 Aspiring Data Professional
🌏 Based in Malaysia
📊 Passionate about using data to solve real-world problems

With a background in biotechnology and scientific reporting, my goal is to bridge scientific rigor and analytical creativity — using data to explain why things happen and predict what happens next.

I’ve built and analyzed models across industries — from customer churn and insurance claims to content engagement and agricultural yield. I’m driven by curiosity, structure, and the impact data can make when translated into real-world decisions.

• Languages & Tools: Python, R, SQL, Excel, Git, PowerBI
• Libraries: pandas, NumPy, scikit-learn, Matplotlib, Seaborn
• Techniques: EDA, Classification, Clustering, Regression, Hypothesis Testing, PCA
• Other: Agile, Google-Certified Project Management, Scientific Documentation

🔹 Logistics Inventory Data Analysis (SQL + PowerBI)

SQL and Power BI analysis of shipment lead times, delay rates, inventory days, and SKU performance for a retail logistics context.

🔹 Recipe Site Traffic Prediction (Machine Learning + KPI)

Classified high-traffic recipes using Logistic Regression, Decision Tree, and Random Forest. Defined a business KPI — High Traffic Conversion Rate (HTCR) — to align model precision with strategy. → Best Model: Logistic Regression (Precision = 0.88, HTCR = 7.13)

🔹 Telecom Customer Churn Analysis

Predictive model to identify customers at risk of churn using billing and usage patterns.
F1 Score: 0.85 | Key tools: Python, Random Forest, Seaborn_

🔹 Insurance Claim Outcome Modeling

Built classifiers to predict insurance claims and explored risk segmentation.
Accuracy > 75% | SMOTE for class balancing_

🔹 Netflix Content Trends

EDA and visualization of global trends across genres, ratings, and durations.
Clear dashboards to support content strategy decisions_

🔹 Penguin Clustering (PCA + K-Means)

Unsupervised learning project to classify species based on biometric traits.

🔹 Crop Yield Prediction (Regression)

Modeled yield based on environmental factors to support precision agriculture.

🧠 More projects available in the Repositories

• Streamlit & dashboard deployment
• Data storytelling with Tableau and Power BI
• Model interpretability (SHAP, feature importance)
• Data pipelines & workflow automation

• 📧 Email: yievia@gmail.com
• 🗂️ DataCamp Portfolio: View Here

Thanks for visiting! Let’s connect and collaborate on impactful data projects!