Esports Charts - Ukrainian IT company that develops world-known esports services.
We collect viewership statistics of all live broadcasts worldwide and create unique analytics.
A few facts:
- We provide data to teams, tournament operators and game publishers all over the planet
- We deal with tables up to 50 billion rows, filling them with data from 29 platforms
- Most detailed statistics about streaming, that you can find in web, appear in our office
We are looking for a ML/Data Scientist to join the existing team and help us to improve our data-management processes, make our metrics even more precise.
By now, we have a lot of big tables (>10 billion rows, up to 50) that shows the statistics of streams' viewership, chat activity and everything we can scrap. Moreover, we have tools for quick and sharp data management, web interface for most of usual tasks. Based on this statistics, we create a lot of metrics that are further analyzed. Although, we make a lot of forecasting now, we wan't to extend our prediction range and make it more precise. Examples of what we want to know - who will be more famous in a year in China - OG or Liquid, how popular the tournament will be if the teams are already known.
On the other hand, we make steps in ML logo and text recognition but we still have a lot to do, so we hope our new colleague, experienced ML/Data Scientist will help us on our way.
What we think is important:
- Two years of data analytics experience
- Deep understanding of SQL-like databases
- More than a year of experience with R / Python
- Strong analytical skills - you have to analyze relationships and dependencies, look for the causes of data correlation
Will be a plus:
- Master's degree in technical specialty or economic cybernetics
- Experience with Jupyter or similar environments
- Experience with analytic and/or ML libraries - NumPy, Pandas, Scikit-learn, TensorFlow
- Background in game dev and/or view analytics
Tasks we'll do everyday:
- Prepare reports for partners based on ready-made database queries
- Approximate the required values
- Find and scrap missing data
- Work closely with the development team on scraping new data, understanding existing one
The way we hire:
Each CV is checked by Tech Lead and HR. In case you have relevant experience, HR will contact you for a zoom interview, on which we fill the gaps and discuss your previous experience - how and what you worked with.
According to the results of this stage, we invite candidates into our office to pass tech-interview with our CTO. When we understand that you're going our way - we make an offer, if something goes wrong - we give precise feedback.
If you match our requirements, we are always happy to get your CV!