Data science capability across the group is a key enabler for this transformation and has been a high priority since the beginning. Starting from zero some years ago with a single centralized team under the strategy department, the data and analytics organization of today contains teams dedicated to, e.g., personalization, user modeling, user insights, and natural language and image processing. This session will provide some insights from this journey from an operational perspective with an emphasis on data science and engineering.
Questions:
- How can you enable data science teams and their members to be impactful and efficient during periods of high growth and uncertainty?
- How do you balance short-term organizational expectations and needs with long-term strategic priorities from a team perspective?
- Is it possible to build scalable data products and still provide business value along the way?
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