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What will you be doing at Miniclip? Develop and refine pLTV (predicted Lifetime Value) models to optimize user acquisition strategies, ensuring profitable and sustainable growth. Utilize SQL, Python and Pyspark within the Databricks environment to extract, transform, and analyze large datasets, providing actionable insights to the User Acquisition team. Collaborate closely with other s and Analytic Engineers to enhance data pipelines, model accuracy, and reporting capabilities. Proactively identify and resolve data discrepancies and model errors to maintain the integrity and reliability of our pLTV predictions. Communicate complex findings and model performance to stakeholders, answering questions and building a strong understanding of how UA data drives business decisions. Create and maintain dashboards in Looker to visualize key performance indicators and share insights with the wider team. What are we looking for? Proven experience as a Data Scientist, specifically working on predictive models. Experience with performance marketing within mobile gaming or apps (not mandatory). Strong proficiency in Python for data analysis and model development, and SQL for data querying and manipulation. Experience with cloud-based data platforms (e.g. AWS, Databricks) and business intelligence tools such as Looker. A solid grasp of statistical and machine learning concepts, with a focus on time-series analysis or predictive modeling.
Job Responsibility:
Develop and refine pLTV (predicted Lifetime Value) models to optimize user acquisition strategies, ensuring profitable and sustainable growth
Utilize SQL, Python and Pyspark within the Databricks environment to extract, transform, and analyze large datasets, providing actionable insights to the User Acquisition team
Collaborate closely with other s and Analytic Engineers to enhance data pipelines, model accuracy, and reporting capabilities
Proactively identify and resolve data discrepancies and model errors to maintain the integrity and reliability of our pLTV predictions
Communicate complex findings and model performance to stakeholders, answering questions and building a strong understanding of how UA data drives business decisions
Create and maintain dashboards in Looker to visualize key performance indicators and share insights with the wider team
Requirements:
Proven experience as a Data Scientist, specifically working on predictive models
Experience with performance marketing within mobile gaming or apps (not mandatory)
Strong proficiency in Python for data analysis and model development, and SQL for data querying and manipulation
Experience with cloud-based data platforms (e.g. AWS, Databricks) and business intelligence tools such as Looker
A solid grasp of statistical and machine learning concepts, with a focus on time-series analysis or predictive modeling
Nice to have:
Experience with performance marketing within mobile gaming or apps