Our team is building the Data platform to enable capture, upload and processing of telemetry data from millions of end-user and infrastructure systems.
Our data sources include traditional personal computers, servers, mobile devices and distributed Web services. In the next couple of years our client base is going to exceed 100 million users.
Join us now to support this development of the large-scale data collection and analysis platform!
Our active projects include crash and performance tracking of the client applications, user behavior profiling, user base segmentation and campaign targeting, smart personalized recommendations, QoS analysis for game video streaming.
We have even more ideas where your knowledge and your experience are needed. You will be adding intelligence and analysis capabilities to various user-
facing projects, you will help to deliver the power of Data to our users across the world. The scale of the system and the business needs require a combination of batch-
Are you a talented, visionary and ambitious engineer who can help us grow our solutions for the data analysis for millions of gamers from all over the world?
What will you do :
You will come up with scalable algorithms (for data processing and machine learning) on how to diagnose the root causes of errors.
You are expected to understand the results of the algorithms / models and reiterate / enhance the algorithms given the updated results
You will prepare documentation for the processes, policies, data formats, test cases and the expected results within the scope of your projects.
What we need to see :
You will have to drill into the problems of running large scale software in a big network
We need you to possess a strong track record of dealing with time series data
latency services. You have passion for efficient algorithms and data structures, advantages / limitations of using them in distributed environments
Ways to stand out from the crowd :
hands-on experience with NoSQL DBs. Love for PC / mobile gaming will help you in working with our data sets.
Do you have a 'pet' software project? We are happy to see your code examples.