Istanbul, Türkiye
Data Scientist with experience in the digital gaming industry, skilled in machine learning, data analysis, engineering, and visualization tools. Proficient in Python, R, and SQL. Ability to analyze and interpret large datasets, identify trends and patterns, develop data pipelines, and present findings in a clear and concise manner.
Proposed level generation and level difficulty detection algorithms for a mobile game within the match genre. Designed data pipelines using the Databricks data intelligence platform for multiple games. Transformed raw and nested SDK event data into BI-integrated user-level tables. Created daily KPI dashboards to monitor user behaviors and level metrics in casual mobile games belonging to match and io genres.
Built user-specific monetization and engagement strategies based on machine learning classification algorithms. Implemented time-series models to forecast in-game metrics such as the return of add spending (roas), and average revenue per daily active user (arpdau). Used data Airflow platform to build Python-integrated data engineering pipelines that schedule the features such as push notification, and various in-game monetization services.
Sentiment analysis of Turkish tweets by using Deep NLP models. Determined the long-term effects of major public events on social network trends.
Network Science Computational Approaches to Problem Solving Calculus II