Middle Data Scientist

About your key responsibilities and impact:

Formulating hypotheses regarding the requisite data types, actively seeking, and procuring said data from pertinent sources;
Collaborating with subject matter experts across various sports domains to validate hypotheses, discerning impactful factors, and selecting algorithms tailored to specific scenarios;
Engaging in the coding process, encapsulating the constructed model within functional code for validation purposes;
Crafting solutions utilizing Python or the .Net stack, providing detailed algorithmic descriptions, and disseminating them to fellow developers for implementation.

Essential professional experience:

Strong knowledge of SQL (various dialects), experience with MongoDB as a plus;
The ability to retrieve data from other sources, such as parsing (e.g., Selenium), and some experience with Kafka is preferred;
Strong statistics knowledge is key;
Experience with the development of ML models (image processing, pattern recognition, and similar);
Knowledge of Python and its libraries (NumPy, Numba, and multithreading), and experience with .Net are preferred, but not mandatory;
Upper-Intermediate English level.

Desirable skills and personal features: