Game Analyst

The work starts with the data a running game produces: sessions, progression, spending, drop-off. The analyst builds the queries, checks whether a change moved anything, and says what the numbers do and do not support.

SQL is the everyday tool. Economy and monetization design belong to it, because much of the questioning is about rewards, prices and progression curves, and playtesting belongs to it because a number without a played session is hard to interpret. Machine learning comes in where forecasting and segmentation are part of the work.

The role is distinct from a data scientist in a games company: the subject is the game, not the business around it. An analyst who cannot explain a drop-off in design terms will not be useful to the team that has to fix it.