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 data mining and predictive machine learning. My main field of expertise is time series forecasting.
Current Techstack
Python, SQL, Unix, MS Excel
Polars, NumPy, LightGBM, Keras/TensorFlow, scikit-learn
Git, GitHub, GitLab, DVC, Poetry, Conda, PyCharm
AWS (S3, EC2, SageMaker)
Other tools I have experience with:
Java, R, Tidyverse, data.table, MySQL, Hibernate, Maven, Gradle, VBA, ArchUnit
Example Projects
Developing a backtesting infrastructure and creating machine learning trading strategies for the US stock market (work in progress)
Conceptualising and implementing forecasting algorithms for EV charging demand for a German startup
Daily stock market predictions with LightGBM (work in progress)
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