Artwork

Contenu fourni par Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
Player FM - Application Podcast
Mettez-vous hors ligne avec l'application Player FM !

Shir Meir Lador | Using Data Science to Keep Financial Data Secure

35:04
 
Partager
 

Manage episode 264308731 series 2706384
Contenu fourni par Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

In addition to her job at Intuit, Lador is a WiDS ambassador in Israel, has her own podcast about data science, and is a co-founder of PyData Tel Aviv meetups.

Lador’s team at Intuit focuses on machine learning in security and fraud applications to protect customers’ sensitive financial data from fraudsters and hackers. She and her team use anomaly detection and semi-supervised methods to secure Intuit products and data. “In general, putting AI into products is not an easy task.” But she thinks we need to put a lot of effort into securing our data especially with recent data leaks from Equifax and Facebook. “I think the world is going into that direction with the GDPR and other initiatives. AI has a lot of potential of helping in that domain,” she explained during a conversation with Stanford’s Margot Gerritsen, Stanford professor and host of the Women in Data Science podcast.

Israel has a lot of expertise in the security domain because many young people study security and encryption during Israel’s mandatory military service. She had the option to do this during her service, but since she already knew she would pursue a career in this area, instead she chose to become a pilot instructor in the flight simulator. “It was a very unique experience that I would probably never get to do.”

When Lador was starting her career in data science, she did not know many people in the field. She decided to start a PyData branch in Israel because she wanted to build a professional data science community. “My main motivation was that I wanted to learn and that I wanted to have friends and people to consult with and learn from. And now I have so many data scientist friends because of all this work and it's great. I love it.”

She noticed when organizing PyData events that it was much easier to get male speakers. When she would ask a talented female scientist to talk about her work, she would say: “No, I'm not an expert… I'm not ready. I need to learn more… I was like, no, you're enough years in the field. Everyone can learn something from you.”

Being a WiDS ambassador was like an extension of her PyData work. “I get to decide what's in the conference and bring the best talks there.” Her experience organizing the PyData meetups helped her know how to create a valuable conference. She sees WiDS as a great opportunity to encourage more women to speak by giving them a platform, but also by bringing all the people together. “Seeing all those women on stage. This gives great inspiration to speak at other events, not just in WiDS. I think this is just an amazing initiative.”

RELATED LINKS
Connect with Shir Meir Lador on Twitter (@shirmeir86) and LinkedIn
Listen to Shir's podcast Unsupervised
Learn about PyData TelAviv Meetup
Read more about Intuit
Connect with Margot Gerritsen on Twitter (@margootjeg) and LinkedIn
Find out more about Margot on her Stanford Profile
Find out more about Margot on her personal website

  continue reading

53 episodes

Artwork
iconPartager
 
Manage episode 264308731 series 2706384
Contenu fourni par Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

In addition to her job at Intuit, Lador is a WiDS ambassador in Israel, has her own podcast about data science, and is a co-founder of PyData Tel Aviv meetups.

Lador’s team at Intuit focuses on machine learning in security and fraud applications to protect customers’ sensitive financial data from fraudsters and hackers. She and her team use anomaly detection and semi-supervised methods to secure Intuit products and data. “In general, putting AI into products is not an easy task.” But she thinks we need to put a lot of effort into securing our data especially with recent data leaks from Equifax and Facebook. “I think the world is going into that direction with the GDPR and other initiatives. AI has a lot of potential of helping in that domain,” she explained during a conversation with Stanford’s Margot Gerritsen, Stanford professor and host of the Women in Data Science podcast.

Israel has a lot of expertise in the security domain because many young people study security and encryption during Israel’s mandatory military service. She had the option to do this during her service, but since she already knew she would pursue a career in this area, instead she chose to become a pilot instructor in the flight simulator. “It was a very unique experience that I would probably never get to do.”

When Lador was starting her career in data science, she did not know many people in the field. She decided to start a PyData branch in Israel because she wanted to build a professional data science community. “My main motivation was that I wanted to learn and that I wanted to have friends and people to consult with and learn from. And now I have so many data scientist friends because of all this work and it's great. I love it.”

She noticed when organizing PyData events that it was much easier to get male speakers. When she would ask a talented female scientist to talk about her work, she would say: “No, I'm not an expert… I'm not ready. I need to learn more… I was like, no, you're enough years in the field. Everyone can learn something from you.”

Being a WiDS ambassador was like an extension of her PyData work. “I get to decide what's in the conference and bring the best talks there.” Her experience organizing the PyData meetups helped her know how to create a valuable conference. She sees WiDS as a great opportunity to encourage more women to speak by giving them a platform, but also by bringing all the people together. “Seeing all those women on stage. This gives great inspiration to speak at other events, not just in WiDS. I think this is just an amazing initiative.”

RELATED LINKS
Connect with Shir Meir Lador on Twitter (@shirmeir86) and LinkedIn
Listen to Shir's podcast Unsupervised
Learn about PyData TelAviv Meetup
Read more about Intuit
Connect with Margot Gerritsen on Twitter (@margootjeg) and LinkedIn
Find out more about Margot on her Stanford Profile
Find out more about Margot on her personal website

  continue reading

53 episodes

همه قسمت ها

×
 
Loading …

Bienvenue sur Lecteur FM!

Lecteur FM recherche sur Internet des podcasts de haute qualité que vous pourrez apprécier dès maintenant. C'est la meilleure application de podcast et fonctionne sur Android, iPhone et le Web. Inscrivez-vous pour synchroniser les abonnements sur tous les appareils.

 

Guide de référence rapide