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To help us in our mission and vision we are looking for a reporting analyst who can support and guide our teams in using data as a tool in decision making. Are you the one to help us visualize where we are headed?
You will be responsible for visualizing the world of numbers in a way that teams can understand and act upon. By designing and using metrics that correctly captures the direction the teams want to take, you build reports and metrics that enable them to see their progress. You will be highly involved in the OKR (Objective, Key Result) process and enable teams to use data and metrics in their goals.
You will also guide the teams to proactively think about how to use data in their decision-making process by following up on the team’s use of the metrics, holding workshops, and participating in show-and-share sessions. Your visualization skills, together with your ability of explaining metrics to diverse teams will be highly valued in this role.
You will be part of a growing Insights team supporting the Games department in Stockholm. You will collaborate and act as liaison with our colleagues in Redmond.
- Build and maintain reports and metrics for teams across the Games Department.
- Give both written and verbal context to the metrics that are reported.
- Streamline reporting and metrics across teams by leveraging the expertise and tools of the DnA (Data & Analytics) department.
- Hold workshops and sessions to educate and enables the teams to explore and understand metrics that are relevant for their work and realistic to maintain.
- Be a liaison between the Redmond and Stockholm on Franchise OKRs and metric reporting.
- Excellent communication skills, both written and verbally.
- Highly skilled in designing and visualizing metrics using analytical tools (keywords: Power BI, Tableau, QlikSense, Excel, SQL, Python).
- Good foundation in SQL.
- Bonus: Experience in wrangling data. You feel comfortable in getting the data that is needed, in the way you need it. (keywords: R, Python, Databricks).
- Bonus: You appreciate that data isn't everything, and that to get the best results means working cross-functionally and value input from other sources.