
Staff Applied Scientist - Economy
- London
- Permanent
- Full-time
- Serve as the subject matter expert and thought leader, collaborating closely with product, commercial, and dev teams to identify and unlock opportunities for innovation and improvement in game economy design & mechanics.
- Spearhead the development and implementation of econometric, statistical and machine learning models on areas such as virtual economy health, marketplace pricing, micro- and macro-level response to economy setting changes.
- Utilize predictive, simulation and optimization techniques to build out data-driven and farseeing support capabilities on economy tuning, balancing, and intervention decisions.
- Collaborate with other applied scientists and machine learning engineers to deploy and productize your models, integrating with games or streamlining decision-support insights.
- Foster a culture of developing and testing hypotheses through experimentation, and build out causal inference muscle for understanding intervention outcomes.
- Master's or Ph.D. in Economics, Statistics, Marketing Science, Management Science, Operations Research, Industrial Engineering, Computer Science, or a related field.
- 4-6 years of working experience with demonstrated ability in economist, data science, or applied research roles.
- Deep knowledge in microeconomics, macroeconomics, and econometrics.
- Solid experience with developing and implementing statistical, machine learning, and econometric models.
- Proficient in Python or R programming, especially with tasks in data manipulation, analysis, and visualization, as well as statistical and ML modeling. Experienced with SQL, relational database, and large datasets.
- Excellent written and verbal communication skills, including the ability to clearly explain complex economic insights to non-specialist audiences.