Building a Highly Effective People Analytics Team at Barclays | Jésus Rogel-Salazar, Barclays Building a Highly Effective People Analytics Team at Barclays | Jésus Rogel-Salazar, Barclays
Challenges et enjeux lors de l’opérationnalisation de projets data | Showroomprivé, Dataiku Challenges et enjeux lors de l’opérationnalisation de projets data | Showroomprivé, Dataiku
Scaling Data Science for a Global Analytics Team | Chris Kakkanatt, Pfizer Scaling Data Science for a Global Analytics Team | Chris Kakkanatt, Pfizer
Surveillance Platform for Bank Compliance | Mayur Thakur, Goldman Sachs Surveillance Platform for Bank Compliance | Mayur Thakur, Goldman Sachs
Data Science in the Insurance Industry | Perry Beaumont, The Distinguished Programs Group Data Science in the Insurance Industry | Perry Beaumont, The Distinguished Programs Group
Et si on utilisait le pouvoir des algorithmes pour résoudre les problèmes sociaux? | Mickael Fine, Blizzard Entertainment Et si on utilisait le pouvoir des algorithmes pour résoudre les problèmes sociaux? | Mickael Fine, Blizzard Entertainment
Stakeholder Management: A Data Scientist’s Perspective | Denis Fragkakis, IG Index Stakeholder Management: A Data Scientist’s Perspective | Denis Fragkakis, IG Index
Data & Decision Science to Battle Recruiting Bias | Maryam Jahanshahi, TapRecruit Data & Decision Science to Battle Recruiting Bias | Maryam Jahanshahi, TapRecruit
Training Machines to Humanize Dating | Shanshan Ding, Hinge Training Machines to Humanize Dating | Shanshan Ding, Hinge
Comment initier des projets data dans un centre de technologie? | Lucile Baur, Schlumberger Comment initier des projets data dans un centre de technologie? | Lucile Baur, Schlumberger
Ethics, Data Science, and Public Service Media | Ben Fields, BBC News Ethics, Data Science, and Public Service Media | Ben Fields, BBC News
Automate Decision Making to Scale Up Business | Spilios Tzouras, Ferratum Automate Decision Making to Scale Up Business | Spilios Tzouras, Ferratum
L’intelligence Artificielle Responsable Pour un Impact Positif | Bernard Ourghanlian, Microsoft L’intelligence Artificielle Responsable Pour un Impact Positif | Bernard Ourghanlian, Microsoft
Augmented Human Intelligence | Walid Mehanna, Daimler Augmented Human Intelligence | Walid Mehanna, Daimler
Diversity and Inclusion in Data Science | Noelle Silver, HackerU Diversity and Inclusion in Data Science | Noelle Silver, HackerU
Getting from 1 to 100 Users With Dataiku | Roberto Amador, Johnson & Johnson Getting from 1 to 100 Users With Dataiku | Roberto Amador, Johnson & Johnson
Search at GIPHY: Staying on Top of the Zeitgeist | Yael Elmatad, GIPHY Search at GIPHY: Staying on Top of the Zeitgeist | Yael Elmatad, GIPHY
Becoming Data Driven in 10 (Easy) Steps | Kim Nilsson, Pivigo Becoming Data Driven in 10 (Easy) Steps | Kim Nilsson, Pivigo
EGG AMS 2019 Opening Plenary | Hylke Visser, Dataiku EGG AMS 2019 Opening Plenary | Hylke Visser, Dataiku
The Growing Pains, Pitfalls & Future for a Data Science Team in a Hyper-Growth company | Shaun Moate, DAZN The Growing Pains, Pitfalls & Future for a Data Science Team in a Hyper-Growth company | Shaun Moate, DAZN
Are You Vulnerable to Adversarial Machine Learning? | Celeste Fralick, McAfee Are You Vulnerable to Adversarial Machine Learning? | Celeste Fralick, McAfee
Demokratisierung von Data Science bei Mercedes Benz Finance | Statworx, Mercedes Benz Demokratisierung von Data Science bei Mercedes Benz Finance | Statworx, Mercedes Benz
Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku
Synthetic Data: How Do We Manage Them? | Armando Vieira, Hazy Synthetic Data: How Do We Manage Them? | Armando Vieira, Hazy