Game Economist

Hitapps

WorldwideremotePosted 1 month ago

Skill Required

Game-EconomistGameAnalyticsGame-DesignData-ScienceBusiness-IntelligenceGame-Economy-DesignerGame-EconomyGame-Economy-DesignGame-MathematicianGame-Strategy-AnalystExcelEngineeringStatisticsanalyticalPythonTableauLookerdesignSQLandMachine LearningFulltime

Key highlights

Minimum 5 years of relevant work experience in game development.
Bachelor’s degree in Statistics, Math, Engineering, Economics, or related quantitative field.
Strong analytical and problem‑solving skills with high attention to detail.
Advanced proficiency in Excel and SQL for large data sets.
Experience with statistical tools (R, SAS, Python) and BI platforms (Tableau, Looker).
Passion for social gaming behavior and tolerance for ambiguity.

Role overview

Responsibilities

Design the user experience from an economic point of view, trying to predict the players' behavior according to the data we already have;
Price the game's virtual currencies;
Build simulations and predictive models to forecast the results of changes to the content proactively;
Work with product teams on balancing new features;
Monitor individual and macro player balances to ensure the overall health of the game's economy;
Analyze large, complex data sets to address strategic and operational business decisions.

Requirements

Relevant work experience in similar positions for at least 5 years in the game development industry;
BA/B.Sc. in Statistics / Math / Engineering / Economy or other quantitative fields;
High-level analytical and problem-solving skills with strong attention to details;
Excellent communication skills – someone who can turn complex concepts into actionable recommendations;
A true passion for understanding consumers' social gaming behavior and tolerance for ambiguity;
Advanced Excel knowledge, including data manipulation, etc;
A strong interest in games;
Strong SQL experience that includes querying large and complex data sets;
Previous analytical work experience, preferably in the Gaming industry;
Advanced knowledge in statistical tools and models (R, SAS, Python);
Experience in BI tools such as Tableau and Looker;
ML knowledge.