Award winning games development studio who are famous for their mobile titles and have worked with some of the leading publishers all over the world. Are looking for Junior level Data analyst to join their team in Europe.
PLEASE NOTE to be successfully selected you must have either a PHD/ Masters in Datascience or Data Analytics and ideally have some level of experience in terms of commercial Data in the field or as a Consultant or Researcher in Data Projects.
The mobile games frenzy has flooded my client with data and they are looking for looking talented Games Analysts to provide key insights into the development and servicing of our titles. By drilling down into data and running experiments you’ll be optimising the experience to keep people coming back.
You’ll work within a small, yet passionate team of Analysts Combining science, data and the creative elements to service titles played by millions.
Responsibilities will include:
· Developing game-specific analytics to accurately measure user play.
· Researching, modelling and optimisation of game features such as in-game economies, upgrade paths, monetisation and difficulty balancing.
· Collecting, analysing and interpreting data to identify player pain-points and interests.
· Devising, implementing and running AB tests on live games.
· Working productively within the project teams to ensure the results of analyses are communicated.
Skills will ideally include;
· Degree in mathematics, statistics, computer science or similar relevant subject where you have developed your skills in quantitative analysis.
· A natural ability to translate experiments and analyses into insights.
· Experience in dealing with large, real-world datasets.
· Software engineering skills, in languages such as Java, cpp, R, SQL, Python etc. ( some not all)
· A love for mobile games!
To apply please send CV to firstname.lastname@example.org or tel Sarah on 020 7580 6018 for a confidential chat (once we have your cv). We value close, personal relationships with our candidates and applications by this method tend to be more successful.
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