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1 Rathbone Square, Fitzrovia, London W1T 1FB, UK


6:15 PM - 9:00 PM


Facebook London

DSF Day 3 – Data Science in Media hosted by Facebook

Facebook London @
6:15 pm-
9:00 pm
April 10th , 2019, Wednesday

DSF Day 3 – Data Science in Media hosted by Facebook

Join Data Science Festival London, in partnership with Facebook this April. The evening will consist of 4 lightning talks and a panel discussion on how Data Science is impacting media and online content industry.

Please click here to apply for a ticket: GET TICKETS


6.15pm – Doors open

6:45pm- Lightning talks (4 x speakers: 10mins each)

7:30pm – Panel chat hosted by David Loughlan – Changing approaches and how DS is influencing the media industry.

8.15pm – Drinks, food and networking

9.00pm – Close

Speaker 1: Hervé Schnegg – Lead Data Scientist – The Telegraph

Speaker 2: Miriam Redi – Research Scientist – Wikimedia Foundation

Speaker 3: Adi Masas – Data Scientist – Facebook

Speaker 4: TBC

Due to the popularity of Data Science Festival events, we are now allocating event tickets via a random ballot. Registering here enters you into the ticket ballot for the Data Science Festival Event at Facebook on April 10th 2019, the ballot will be drawn on the 1st April 2019. Those randomly selected will then be e-mailed tickets for the event, with the joining details.

If you get an allocated ticket, please bring a copy of your paper ticket or your ticket on your phone to the event to check in with your QR code. Tickets are non-transferable.

The Data Science Festival is the first of its kind as the only community-led, free to attend Data Science Festival in the UK.

Adi Masad
Talk Abstract: Product Experimentation At Facebook controlled experiments (AB testing) are a core component in decision making. We use them not only to choose between alternatives, but also to prove or negate our core hypotheses. The importance of experiments and Facebook’s scale means we want all engineers to be able…
Hervé Schnegg
The Telegraph
Talk Abstract: How to evaluate recommender systems? Recommender systems allow us to build personalised experience for our users. But do we know how to evaluate them? Bio: Principal Data Scientist at The Telegraph. Interested in data mining, machine learning and predictive analytics. Developed news recommender systems, churn models and various…
Miriam Redi
Wikimedia Foundation
Bio: Miriam Redi is a Research Scientist at the Wikimedia Foundation and Visiting Research Fellow at King’s College London. Formerly, she worked as a Research Scientist at Yahoo Labs in Barcelona and Nokia Bell Labs in Cambridge. She received her PhD from EURECOM, Sophia Antipolis. She conducts research in social…