Women in Data Science

Conference 2018

Tuesday, March 20, 2018

ZURICH, Switzerland









Women in Data Sciences Zurich (WiDS) is a one day technical conference. It will feature engineering and business leaders from Google, McKinsey, Allianz, Microsoft, Credit Suisse and IBM, among others. It aims to inspire and educate data scientists worldwide, regardless of gender, and support the women in the field. Originally started at Stanford, USA, the conference has spread to more than 100 locations and will reach 50+ countries in 2018, with an online audience of more than 75,000 people last year. Join us for a one day of great keynotes, enlightening tech talks, an inspiring panel discussion and a mentorship lunch session. A limited number of travel grants are available.


What is "women in data science zurich" about?

A one day technical conference about different problems being tackled by data science.  Join us for keynotes, tech talks, a panel discussion and a mentorship lunch session. 

Who are we looking forward to welcome as attendees?

Anyone with an interest in data science is welcome, including university students using data science and machine learning as tools, young professionals in biotech, finance, agriculture, transportation, healthcare or any field that requires understanding and working with data, experienced professionals in these fields and academics working on topics related to data science.

Who will be speaking?

We have a great lineup of speakers from academia and industry. Our keynotes are: Javiera Guedes, senior data scientist at Credit Suisse, Danielle Belgrave, working on disease progression modelling at Microsoft Research, Tilke Judd, working on the Google Assistant and  Gemma Garriga, global head of advanced business analytics at Allianz.

Find out more information about all of our speakers!

How much does the entry cost?

Tickets are 15 CHF and are available here!

Why are we called Women in Data Science?

All of our speakers are women, but all genders are welcome to attend.

 Department of Computer Science

Department of Computer Science