Description

We're looking for an experienced analyst to whom we can entrust product development, establishing a robust data management system, enhancing processes, and providing business consulting on growth opportunities. By solving complex analytical tasks with us, you'll directly influence the development of global hits in mobile game development.

While you'll engage in the classic tasks of any game product analyst—analyzing game economy, balance, player behavior, and more—your most fundamental and important role will be to ensure decision-making processes that lead to sustainable, long-term product development.

What You'll Do

Behind every product is a strong analytics team, and you'll interact with them, but also much broader. Beyond the classic game product analyst tasks, you'll also be responsible for:

• Developing player segmentation to adapt gameplay to the user experience.
• Conducting analysis, preparing reports, and providing recommendations for changing games within the product team.
• Organizing the collection and automated processing of all collected game data, and developing dashboards for recurring reports.
• Participating in the preparation and conduct of A/B testing.

Our Stack

You'll work with a modern stack that's reusable across companies, meaning your skills gained here will remain highly valuable:

• JupyterHub or Databricks + PySpark
• No restrictions on tools; resources are allocated quickly, and we have full access to AWS.
• Data is collected through Appsflyer (marketing) and Amplitude (product).
• Raw data is stored in S3, ETL processes are managed by Airflow, and prepared tables and views are stored in Redshift.
• Data Quality, lineage, and cataloging are managed through Monte Carlo.
• Analysts manipulate data using SQL and Python in Jupyter/Databricks notebooks, and they prototype dashboards using Tableau.
• We're developing self-service and analytical products for data consumers, relieving analysts of routine tasks.

What You'll Need

• Excellent mathematical background — knowledge of probability theory and applied statistics at the level of a technical university graduate.
• Experience in data analysis, product/marketing analytics.
• Excellent knowledge and experience working with SQL.
• Experience working with Python.
• Experience in ML (Machine Learning) would also be very useful.
• Business-oriented, with the ability to find practical solutions in limited time and avoid unnecessary overcomplication.
• A proactive stance, ability and willingness to take responsibility for results, and the ability to act effectively in situations of uncertainty.

Skills and competencies show up in different forms and can be based on different experiences, so we strongly encourage you to apply even if you don't have all the requirements listed above.