Senior Data Analyst

hace 1 mes


Barcelona, Barcelona, España Playvalve A tiempo completo
About Playvalve

Playvalve is a dynamic and innovative gaming studio that is shaping the future of the industry. Our mission is to create engaging and immersive games that bring joy to millions of players worldwide.

We are a team of experts who are passionate about what we do, and we are committed to delivering high-quality experiences that exceed our players' expectations.

About the Role

We are seeking a highly skilled Senior Data Analyst to join our team. As a Senior Data Analyst, you will be responsible for developing and maintaining our data analytics strategy, and you will work closely with our marketing, product, and tech teams to provide actionable insights that drive business growth.

You will have the opportunity to work on mobile games that are played by millions of players around the world, and you will be responsible for analyzing large datasets to identify trends and opportunities for improvement.

Key Responsibilities

  1. Analyze large datasets to generate actionable insights and support data-driven decision-making across various departments.
  2. Develop and maintain key performance indicators (KPIs) and dashboards to monitor the health and performance of our games.
  3. Design, implement, and evaluate A/B tests and other experiments to optimize game features and user acquisition campaigns.
  4. Collaborate with cross-functional teams to translate data insights into recommendations for product improvements and new features.
  5. Draw meaningful conclusions and provide actionable insights from data to shape and influence business growth.
  6. Create and present data-driven reports to inform stakeholders on product performance and user behavior.
  7. Implement and maintain data pipelines, ETL processes, and database systems to ensure data quality and integrity.

Requirements

  • 5+ years of experience in data analysis in mobile gaming (Android & iOS).
  • Strong proficiency in SQL and experience with data visualization tools such as Looker, Datastudio, Tableau, or Power BI.
  • Knowledge of statistical analysis techniques, such as regression, clustering, and hypothesis testing.
  • Experience with programming languages, such as Python or R, for data manipulation and analysis.

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