Hi, I’m Suci
I have background in Environmental Engineering and am currently building my career in data analytics and data science
I believe that good data leads to better decisions and meaningful impact. Through my project experience, I work with data to explore patterns, build predictions, and translate analysis into insights that support real-world problem solving.
Coming from an environmental engineering background, I am particularly interested in applying data science to environmental challenges, while also being open to cross-domain applications in other industries. I started learning data science in 2025 and now pursuing a career in this field.
Technical & Professional Skill
Featured Projects
Water Pump Failure Prediction in Tanzania
End-to-End | Sosial Impact | Machine Learning
Datase: Tanzania Water Pump Dataset
Highlights:
- Framed a real-world infrastructure problem impacting access to clean water in rural Tanzania
- Designed an end-to-end machine learning pipeline covering data cleaning, EDA, feature engineering, and modeling
- Built and evaluated multi-class classification models to predict water pump operational status
- Identified key geospatial and technical drivers of pump failure
- Translated model outputs into actionable insights for maintenance prioritization and resource allocation
Key Skills Demonstrated:
- Problem framing & business understanding
- Supervised learning (classification)
- Feature engineering & model evaluation
- Decision-oriented insight generation
Project Summary
Mini Case Studies
The following case study demonstrate analitical capability, insight generation, and data storytelling.
Regularized Regression for Housing Prediction
- Skill Focus: Regression Modeling · Ridge & Lasso Regularization · Feature Selection · Model Evaluation
- Dataset: Boston Housing Dataset
- Tools: Python, Pandas, NumPy, Scikit-learn, Matplotlib
- Project Link
Professional Certifications