We are growing fast and looking to find experienced developers to join our great team at our one of a kind office at the top floor of Södra Teatern!
Whether you are passionate about tech, esports or both we can offer a unique opportunity to build state of the art computer vision applications and prediction models in a fast moving business. We're looking for someone that wants to be challenged and want to challenge us, someone passionate about technology and motivated to see both yourself and the team as a whole grow and excel!
Outside of day-to-day tasks we also engage in internal "show and tells" between members of team that work with new and interesting technologies and problems. We also have strong culture of social activities in and around the office, with Södra Teatern as our playing ground which offers some truly unique events especially in the summer time when there are live concerts in the evening just outside our balconies. Things like coffee, tea, snacks and fruits are of course always available for free and the views from the office are an unmatched way to wind down when needed!
Our data science team face a lot of novel and interesting challenges. We are looking for a data scientist who is driven by the challenge of building robust and performant applications, where “best in class” is the given standard to go by. It is also important that you are open to new challenges and have a willingness to learn from colleagues as well as research new topics on your own as needed.
Some of the technologies and problems you will work with are:
- Machine learning & deep neural networks
- Text recognition and image processing
- Player and team rating
- Match outcome prediction (and prediction of other events)
- Python programming with modern ML libraries
- State of the art cloud based infrastructure
- Building your own data pipelines
Here are some applications you will work with:
Where ingestion of raw server data is not an option, we use computer vision on the live video streams to automatically extract data. This allows us to get a lot more data than what any human could log throughout a match, faster and with higher accuracy. While it does not make the same amount of data available at the same latency as server access would, it is quite a powerful solution that can drive lots of interesting applications.
Probability Networks & Performance Rating
With all the data we are sitting on, we have a great foundation to try to find answers to “who is going to win the next match?”, “what constitutes a good or bad player performance in a game?” or "what is an effective player constitution for a team". We approach these questions and more with classical modelling, pure algorithms as well as ML/AI approaches.