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People (3 results)
Activities & events
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Causal inference at dunnhumby: how we are applying causal methods in retail data science, key tips and learnings.
2025-06-04 · 17:00
dr dimitra mimie liotsiou
– Senior Research Data Scientist
@ dunnhumby
It is well known in data science that ‘correlation is not causation’. However, standard data science and machine learning methods are about correlation, not causation. Therefore, to answer questions about cause and effect (e.g. about measuring impacts, uplift, or about why a KPI moved), which are central to many data science projects across sectors, a new, causal, approach is needed, of which the standard data science methods are just one part. In this talk, I will show how we are using the new science of graphical causal inference at dunnhumby to answer cause and effect questions in retail, and I will share key tips and learnings. |
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High-quality experimentation at Deliveroo: The vision, implementation and reflection
2025-06-04 · 17:00
ella johnson watts
– Staff Data Scientist
@ Deliveroo
Over the last decade, Deliveroo has built a culture of running high-quality experiments. This talk reflects on Deliveroo’s experimentation journey, from the initial vision to what we have achieved so far with some key lessons for low-cost democratised experimentation at-scale. |
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Advanced SQL – top tips for dealing with real world data
2025-06-04 · 17:00
lydia monnington
– Data Science Lead
@ Google Deepmind
Level up your SQL knowledge to deliver results in real world situations. I’ll cover:
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Fraud Prevention at Deliveroo – the role of Science and key challenges.
2025-06-04 · 17:00
susan blaszczak
– Staff Data Scientist
@ Deliveroo
Fraud prevention is a significant challenge for a platform like Deliveroo and this talk is all about how data science can help. I’ll talk about some of the key fraudulent behaviours we try to tackle and dive into the tricky parts – balancing stringent fraud prevention measures with a seamless user experience and the inherent difficulty in establishing ground truth for fraudulent behaviours. |
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