GameAnalytics is the #1 free analytics tool designed to help game developers and publishers drive conversions, refine critical flows, and boost retention for their titles by making the right decisions based on data. Currently, 17,000+ game developers use GameAnalytics to track performance in 38,000+ titles around the globe.
This means we have incredible coverage – at present we track the behaviour of 600+ million players every month. By joining the team, you’ll help shape the development of an industry leading SaaS platform in one of the most exciting and highest growth verticals on mobile. We are a truly international company with a strong presence in Europe, the Americas and – through our parent company Mobvista – Asia.
About the Data team
You’ll be given the resources and data to learn what makes games go all the way from soft launch to industry hit, and the opportunity to help us engage our passionate community in a sector that’s seeing amazing growth.
This is a great opportunity for Data Scientists with an interest in Machine Learning algorithms, as the Data Team is currently developing new predictive features, and knowledge transfer is one of our core values. As the largest games analytical firm globally, collecting ~100,000 events per second, resulting in new 700GB of (compressed) new data per day!
- Work closely with our product team to develop new and interesting features for our core analytics platform.
- Build solutions for but not limited to: customer segmentation and targeting, propensity modeling, churn modeling, lifetime value estimation, forecasting, recommendation systems, modeling response to incentives, and price optimization
- Ad-hoc analysis of game data and presenting results in a clear manner.
- Provide testing techniques and methodologies in order to assess impact and effectiveness of business initiatives.
- Prototype new ways to visualise and understand data relationships
Skills and Qualifications
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Excellent applied statistics skills, such as distributions, statistical testing, regression, etc.
- Experience with common data science toolkits, such as R, Weka, NumPy, MatLab. Excellence in at least one of these is highly desirable
- Great communication skills
- An expert in SQL and RDBMS concepts, including experience in working with large data sets
- Good scripting and programming skills using languages like Java, Scala, Python, R or Perl.
- Experience working with data pipelines and modeling in a production environment
- Experience of visually communicating results and working alongside designers
Flexible working environment
Always feel refreshed with ample holiday days and a flexible remote working policy.
Expensable phone bill
We all use our mobile phone at work, so we make sure to cover those expenses.