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(BALLOT TICKET) Data Science Festival Day 4-Autonomous driving and Big Data

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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 Parkopedia on Thursday 27th April 2017, the ballot will be drawn on the 20th April 2017. Those randomly selected will then be e-mailed tickets for the event, with the joining details.

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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 Parkopedia on Thursday 27th April 2017, the ballot will be drawn on the 20th April 2017. Those randomly selected will then be e-mailed tickets for the event, with the joining details.
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Data Science Festival Parkopedia Event (Ballot ticket only)

Venue near London Bridge

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 Parkopedia on Thursday 27th April 2017, the ballot will be drawn on the 20th April 2017. Those randomly selected will then be e-mailed tickets for the event, with the joining details.

Schedule:

6:00pm - 6:30pm - Doors Open

6:30pm - 7:15pm - Talk - David Foster

7:15pm - 7:45pm - Break - Beer & Pizza

7:45pm - 8:30pm - Talk -Sanaz Vafaei

8:30pm-9:00pm - Networking and close


David Foster: Data Science Embedded

How do data scientists generate revenue? Answer: generally, they don’t – it’s the actions taken by the wider business following recommendations from data scientists that affect the bottom line. That’s why fully embedding the output from your data science team into every business function isn’t just a ‘nice to have’ – it’s essential. And it’s not easy to achieve - all too often, the impact of data science is lost because the final step, embedding the project into business as usual, is missing.

We will explore this idea in the context of three case studies – an interactive funnel analysis tool called Pathfinder that assesses user flow through a website; user segmentation by behaviour and a churn prediction model that drives targeted ‘smart’ offers. The Data Science Business Map will also be presented as a framework to ensure your business experiences the full range of solutions that data science can offer and we’ll explore the common pitfalls with implementation and how to avoid them.

Bio: David is co-founder of Applied Data Science, a London based data science consultancy delivering practical data science solutions with measurable business value. Previously David was the Senior Data Scientist at Findmypast and has experience developing and managing several high-value data science projects including the algorithm for the negotiation engine used by the local and national sales teams at Global, a media and entertainment company. He has won international machine learning competitions and is an active participant in the online data science community.

In his spare time, David enjoys board games and pub quizzes. He has won the TV show Pointless, though made a fool of himself by thinking that Patrick Swayze sang ‘Dancing in the Dark’. He holds an MA in Mathematics from Trinity College, Cambridge and an MSc in Operational Research from the University of Warwick.

Sanaz Vafaei: 'Where can I park?

This is a question asked too often and by too many drivers. In a busy city, searching for a free parking space can be very frustrating. At Parkopedia we are focused on solving various parking related problems. Parkopedia is the world's largest parking information provider, enabling drivers to find detailed information about millions of parking spaces worldwide. The size and diversity of the data available today allows our researchers to build models to accurately predict availability for these parking spaces. In this talk I will go over the various data sources we use including Ultra Sonic Sensor data, explain some of the data science techniques we apply and discuss how we answer the parking availability question.

Bio: Sanaz Vafaei is a former astrophysicists, turned data scientist. She received her PhD in Physics from University of British Columbia in Vancouver, Canada. She spent many years researching dark matter properties in space through gravitational lensing. After leaving academia and moving to London she started applying many of the same techniques to datasets in the commercial space. Sanaz is now one of the data scientists working in the research team of Parkopedia: the world’s largest parking service provider with the mission of being able to answer any parking question, anywhere in the world. In this talk, Sanaz will be presenting examples of how data science can help achieve this goal.

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