As a data science freelancer, I help people gain meaningful, reliable, and actionable insights from data in a perceptive, diligent, and responsible way. I leverage my broad experience in econometrics, machine learning, and software engineering to offer comprehensive solutions in predictive machine learning, data mining and visualisation, and beyond.
Current Techstack
Python, R, SQL, Unix, MS Excel
Pandas, LightGBM, Keras, Tidyverse, NumPy
Git, GitHub, DVC, Conda, PyCharm
Example Projects
Conceptualising and implementing forecasting algorithms for EV charging demand (work in progress)
Development of a new Python library for interpretable machine learning (work in progress)
Daily stock market predictions (work in progress)
Interactive map visualisation with Leaflet (see below)
Prediction of sales and their uncertainty distributions (Kaggle bronze medal)
Shiny dashboards
Fuzzy matching of names
Derivation, analysis, and visualisation of financial cycles
Correcting labour market flows for instantaneous probabilities
Top 1% wealth shares (2021)