MARKETING DATA SCIENCE

A Technical Event For Technical People

A Technical Event
For Technical People

Thursday, April 12th
18:00 – 21:30

 

Hosted By
Facebook Logo

Stay Updated

MARKETING
DATA SCIENCE

Technical Events For Technical People

A Technical Event For Technical People
Thursday, April 12th
18:00 – 21:30

 

Hosted By

Stay Updated

A technical event for technical people, studying the actual methods behind organisational implementation of data science for more intelligent marketing.

FIVE INDUSTRY CASE STUDIES
KEY NETWORKING
LOTS OF CONTENT

This is a learning event in partnership with Facebook. No high-level vagueness, just powerful insights for you.

Themes:
{Marketing Analytics} {Automation} {Machine Learning} {Customer Intelligence}

A technical event for technical people, studying the actual methods behind organisational implementation of data science for more intelligent marketing.

FIVE INDUSTRY CASE STUDIES
KEY NETWORKING
LOTS OF CONTENT

This is a learning event in partnership with Facebook. No high-level vagueness, just powerful insights for you.

Themes:
{Marketing Analytics} {Automation} {Machine Learning} {Customer Intelligence}

Event Schedule

18:00
Check-In & Networking


———

18:50 – 19:10
Interesting Boring Problems In Marketing Analytics

Paolo Zoccante, Farfetch
Paolo Zoccante, Data Scientist, Farfetch


———

19:10 – 19:20
Attribution Modelling for Acquisitions

Giacomo Giussani, Deliveroo
Giacomo Giussani, Data Scientist, Deliveroo

Key Takeaways

Talk:

– The importance of Attribution Modelling for Marketing.
– Getting the right data: Events tracking and impressions data.
– Combining data: Attribution Models Choice.
– Insights from Data: Marketing Channels ROI and optimisation.


———

19:20 – 19:30
CLV Modelling at Deliveroo

Clemente Iraci, Deliveroo
Clemente Iraci, Data Scientist, Deliveroo

Key Takeaways

Talk:
– CLV model structure and possible approaches.
– Why CLV prediction can be a tricky problem.


———

19:30 – 19:50
Networking Break


———

19:50 – 20:10
Using ML for Real-Time Bidding at HomeAway

Will Funnell, HomeAway
Will Funnell, Principal Engineer, HomeAway

Key Takeaways

Talk:
– Overview of HomeAway’s Marketing challenges.
– How to productionize ML systems reliably.
– How to combine forces with Data Science.
– Mitigate uncertainty on ROAS campaigns.


———

20:10 – 20:30
Facebook’s Auction

Kathy Dykeman, Facebook
Kathy Dykeman, Director of Marketing Science, Facebook


———

20:30 – 21:30
Networking & Drinks

This is your chance to meet the speakers and your fellow machine learning enthusiasts, making connections that go well beyond this evening!

Event Schedule

Check-In & Networking
18:00

Paolo Zoccante, Farfetch

Interesting Boring Problems In Marketing Analytics
Paolo Zoccante, Data Scientist, Farfetch
18:50 – 19:10
LinkedIn

Giacomo Giussani, Deliveroo

Attribution Modelling for Acquisitions
Giacomo Giussani, Data Scientist, Deliveroo
19:10 – 19:20
LinkedIn

Key Takeaways

Talk:

– The importance of Attribution Modelling for Marketing.
– Getting the right data: Events tracking and impressions data.
– Combining data: Attribution Models Choice.
– Insights from Data: Marketing Channels ROI and optimisation.

Clemente Iraci, Deliveroo

CLV Modelling at Deliveroo
Clemente Iraci, Data Scientist, Deliveroo
19:20 – 19:30
LinkedIn

Key Takeaways

Talk:
– CLV model structure and possible approaches.
– Why CLV prediction can be a tricky problem.

Networking Break
19:30 – 19:50

Will Funnell, HomeAway

Using ML for Real-Time Bidding at HomeAway
Will Funnell, Principal Engineer, HomeAway
19:50 – 20:10
LinkedIn

Key Takeaways

Talk:
– Overview of HomeAway’s Marketing challenges.
– How to productionize ML systems reliably.
– How to combine forces with Data Science.
– Mitigate uncertainty on ROAS campaigns.

Kathy Dykeman, Facebook

Facebook’s Auction
Kathy Dykeman, Director of Marketing Science, Facebook
20:10 – 20:30
LinkedIn

Networking & Drinks
20:30 – 21:30

Ticket Registration

Feb 8th: Machine Learning in Production

Continuous Machine Learning Model Deployment
Stephen Whitworth, Co-Founder
Ravelin

Bayesian Change-Point Detection
Paolo Puggioni, ML Data Scientist
Schroders

Dec 7th: Machine Learning

The Inner Workings of Monzo’s Help Search Algorithm
Nigel Ng, Data Scientist, Monzo

Natural Language Processing in Media: Challenges and Opportunities
Xiaolan Sha, Lead Data Scientist, Sky

Ilya Feige, Head of ML Research, SherlockML

Feb 8th: Machine Learning in Production

Continuous Machine Learning Model Deployment
Stephen Whitworth, Co-Founder
Ravelin

Bayesian Change-Point Detection
Paolo Puggioni, ML Data Scientist
Schroders

Dec 7th: Machine Learning

The Inner Workings of Monzo’s Help Search Algorithm
Nigel Ng, Data Scientist, Monzo

Modern Techniques for Dimensional Reduction
Ilya Feige, Head of ML Research, SherlockML

Natural Language Processing in Media: Challenges and Opportunities
Xiaolan Sha, Lead Data Scientist, Sky

Speaker Stories

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