Economics graduate turned Data Analyst, based in Amersfoort, Netherlands. I combine a BSc in Economics and an MSc in Data Analytics to build data-driven insights at the intersection of finance, crypto, and technology.
Languages & Analytics Python · R · SQL · SQLite · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Tableau · Excel
Data Engineering ETL Pipelines · Data Modeling · Data Warehousing · MongoDB · MySQL · CosmosDB · HDFS
Machine Learning Linear & Logistic Regression · Random Forest · Decision Trees · Customer Segmentation · Fraud Detection · Model Validation
Tools Git · GitHub · Jupyter · Anaconda · JIRA · Agile/Scrumban
Analysis of how Bitcoin and Ethereum prices responded to 9 key military escalation events using Python, SQL, and SQLite.
Exploratory data analysis on 7,032 telecom customers to identify the key drivers of churn using Python, Pandas, and Seaborn.
Multiclass classification model predicting ad banner engagement using Random Forest and Decision Trees.
MLR model predicting California median house values from 20,640 observations. R² of 0.597, RMSE of 0.727.
Structured 4-stage learning program covering blockchain payment systems, on-chain data analysis, and real-world payment protocols.
- 📈 Netherlands energy prices & inflation analysis (2024–2026)
- ⛓ On-chain payment data analysis with Dune Analytics
- 🌐 Deepening specialization in crypto/fintech analytics
🇹🇷 Turkish (Native) · 🇬🇧 English (Native) · 🇩🇪 German (A2) · 🇳🇱 Dutch (A1 — improving)
