Conduct undirected research and frame open-ended industry questions for different areas of the business, including but not limited to marketing, credit scoring, and collections to improve business performance in aforementioned areas;
Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modelling;
Explore and examine data from a variety of angles to determine hidden weaknesses, trends and/or opportunities;
Devise data-driven solutions to the most pressing challenges;
Invent new algorithms to solve problems and build new tools to automate work;
Communicate predictions and findings to management and IT departments through effective data visualizations and reports;
Produce relevant documentation related to development process;
Other tasks related to Data Science, assigned by manager.
BSc/MSc in applied statistics, mathematics or equivalent;
Fluent English, both oral and written;
Good programming skills in commonly used statistical programming languages Python, R, and corresponding development environments;
Machine learning tools and techniques (e.g. k-nearest neighbors, random forests, ensemble methods, etc.);
Software engineering skills (e.g. distributed computing, algorithms and data structures);
Data visualization (e.g. ggplot and d3.js) and reporting techniques;
Previous experience of working with scoring modelling is an advantage;
Curious mind and willingness for continuous learning.