About
About Me
I am a Data Scientist and Quantitative Economist with a passion for understanding complex economic systems through data, mathematics, and computational modelling. My work sits at the intersection of economic theory, statistical inference, and modern machine learning.
What I Do
- Econometric Modelling: Causal inference, time series analysis, panel data methods
- Machine Learning: Predictive modelling, feature engineering, model evaluation
- Quantitative Research: Empirical analysis of economic and financial data
- Data Visualization: Translating complex results into clear, actionable insights
Tools & Technologies
- Languages: Python, R, PostgreSQL, Javascript
- ML/AI: scikit-learn, TensorFlow, PyTorch
- Data: pandas, NumPy, Polars, Spark, Dplyr
- Visualization: Ggplot, D3.js, Matplotlib, Seaborn, Plotly
- Other: LaTeX, Hugo, Docker, Git, WSL2
Background
My academic training in economics gave me a strong foundation in theory, statistics, and mathematical reasoning. Working with real-world data taught me that good models require both rigorous methodology and practical intuition.
This blog is where I share my thoughts on economics, statistics, modelling techniques, and the occasional mathematical deep-dive.