Data Science

As a Data Scientist, I have worked on a wide range of projects in different fields.

I am primarily involved in Natural Language Processing (NLP) and all possibilities of using texts in building artificial intelligence systems.

Selected problems I solved using machine learning

• assessing the comprehensibility of Polish legal acts,
• prediction of insurance fraud,
• prediction of transactional fraud,
• exploration of factors affecting the success of advertising campaigns.

In my analyses I use

• basic tools of descriptive statistics,
• tools of inferential statistics: parametric and non-parametric tests,
• regression models: linear, logistic and regularized models,
• single models: e.g. decision trees, support vector machines,
• ensemble learning models: random forests, boosting of all kinds,
• unsupervised learning,
• neural networks,
• natural language processing (NLP).

For research work I use

• Python language (pandas, numpy, matplotlib, scikit-learn, TensorFlow, Keras, selenium, spacy, nltk),
• R language (tidyverse: dplyr, tidyr, ggplot2; tidymodels, tidytext),
• SQL language,
• Excel,
• git for version control,
• markdown writing language.

I am also familiar with, though not in the habit of using

• SAS,
• dashboard software,
• basic html and css.