Back to schedule

Location

120 Holborn, London EC1N 2TD

When

6:00 PM - 9:00 PM

Website

Trainline London



DSF Day 4 – Solving E-commerce challenges with DS hosted by Trainline

Trainline London @
6:00 pm-
9:00 pm
April 11th , 2019, Thursday
Location:

DSF Day 4 – Solving E-commerce challenges with DS hosted by Trainline

Join us for an evening of Data Science talks focused on solving E-commerce challenges. The evening will consist of two talks, one from our hosts Trainline, the other from Marco Bertetti Data Scientist at Skyscanner.

With applications and websites growing more complex than ever, Marco will discuss important new approaches to surface the right content to the right users as many time as possible.

Please click here to apply for a ticket: GET TICKETS

Schedule:

6.00pm – Doors open

6.30pm- Marco Bertetti

7.15pm – Drinks food & networking

7.45pm – Dan Taylor & Sam Taylor

8.30pm – Networking

9.00pm – Close

Address: 120 Holborn, London EC1N 2TD

Marco Bertetti – Data Scientist at Skyscanner

Summary: Contextual multi-armed bandits for widget optimization. Mobile applications and websites are growing more complex than ever, with new graphics, functionalities and widgets being added every day. In this ever-growing space it is important to develop new approaches to surface the right content to the right users as many time as possible. While A/B test is a widely used and solid technique, it is not always viable when the number of possible choices is very large, hundreds or thousands of tests would be required to find the best option for each situation. This talk will firstly provide an introduction to the muti-armed bandit problem. Then, a practical comparison between bandits and classic A/B testing will be shown. Closing with a practical Bandit implementation at Skyscanner.

Bio: Marco Bertetti is a Data Scientist at Skyscanner based in London, who has worked both in using reinforcement learning for mobile app content, and in shaping the structure and integrity of Skyscanner’s logging and data. Before joining Skyscanner, he has worked on different problems for a variety of companies ranging from tech startup to big retailer. He obtained a degree in Globalization, International Institutions and Economic Development at the University of Trento before moving to London. In his free time, he likes photography, cooking and rock climbing.

Dan Taylor – Data Engineering Manager

Bio: Dan runs the Data Engineering team at Trainline.  He’s passionate about applying engineering principles to data products: building cool stuff that _actually runs in production_.  He’s headed up Data Engineering teams in such exciting fields as insurance comparison, telecoms network optimisation and supermarket refrigeration, and asserts that 90% of data challenges are the same across all industries.

Sam Taylor – Lead Machine Learning Engineer

Bio: Sam is the Lead Machine Learning Engineer in the Data Science team at Trainline. He has worked on many of the customer facing data products at Trainline from Price Prediction to BusyBot and recommendation engines. He enjoys deploying data products at scale that positively impact the lives of Trainline’s customers. Previously he has worked in fintech and telecoms, working with machine learning to optimise the customer experience.

Summary:  Enabling Real Time Data Science in E-Commerce. The architecture of modern E-commerce companies typically revolves around micro-services, this often causes a challenge for Data Scientists who need to pull data from disparate sources to carry out their day to day work. This pushes the typical 80% of time spent on data exploration, closer to 100%, resulting in less time spent solving the customer problem. At Trainline, we have solved this using event sourcing and streaming technology. We will talk about how this is practically carried out from a data engineering to data product development perspective. We will then explore advancing this technology, giving the ability to put realtime data products into production and the hands of our customers.

 Please review how the tickets work here:

http://2019.datasciencefestival.com/dsf-tickets-101/

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 COMPANY on April 11th 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.

Dan Taylor
Trainline
VIEW BIO
Talk Abstract: The architecture of modern E-commerce companies typically revolves around micro-services, this often causes a challenge for Data Scientists who need to pull data from disparate sources to carry out their day to day work. This pushes the typical 80% of time spent on data exploration, closer to 100%,…
Marco Bertetti
Skyscanner
VIEW BIO
Talk Abstract: Contextual multi-armed bandits for widget optimization. Mobile applications and websites are growing more complex than ever, with new graphics, functionalities and widgets being added every day. In this ever-growing space it is important to develop new approaches to surface the right content to the right users as many…
Sam Taylor
Trainline
VIEW BIO
Talk Abstract: The architecture of modern E-commerce companies typically revolves around micro-services, this often causes a challenge for Data Scientists who need to pull data from disparate sources to carry out their day to day work. This pushes the typical 80% of time spent on data exploration, closer to 100%,…