- Explore: Understand our stakeholders needs & main pain points and leverage data to identify opportunities to improve business, optimize our products and create data assets. For that purpose, develop a deep understanding of our products & ecosystem, as well as a deep knowledge of the data lifecycle.
- Empower: Evangelize on the use of data in the company, train colleagues on analytics tools, build automated dashboards and assets to enable stakeholders to be as autonomous as possible with data.
- Measure: Analyze the impact of product releases on business metrics, as well as their impacts on products performances.
- Collaborate: Contribute to an iterative process of product improvement, collaborating seamlessly with cross-functional teams (engineers, developers, data scientists & analysts, product & business)
- Communicate: Share findings through clear visualizations, engaging presentations and straight to the point recommendations.
Examples of data assets: internal analytics platform, new data pipeline, AB test analysis framework, forecast model…
Examples of analyses use cases: video recommendation models, search algorithms, supply optimization, player performances optimization, ...
Our stack
- Data Lake in Google Big Query: writing complex SQL queries is a daily practice (+ using R and Python for specific needs)
- Tableau and Looker Studio for data visualizations and dashboards
- Internal A/B testing tool (Python based)
Additional InformationWhat we offer you:
• Additional opportunities as we grow and learn together.
• Join our open, collaborative culture.
• Exciting, dynamic projects to work on.
• Flexibility.
For the France offices
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