Irit Opher &
Rachel Lemberg

How to Avoid ‘Re-inventing the Wheel’ Syndrome in Data Science
Microsoft

Talia Tron & Liat
Ben Porat

Customer-driven AI: Making Sure Your Model Suits Your Customer Needs

Microsoft

Bio

Irit is a research manager specializing in Machine Learning and Speech Recognition, with 20 years’ experience in Israel’s high-tech Industry.
Her experience includes algorithm development and research in various domains, including speech and speaker recognition, data analysis, text analysis, classification and clustering methods and neural networks.


She is passionate about data of all types, and approaches any new data with respect.
She has led many R&D projects from conception to successful deployment at customers’ sites, and managed various collaborative research projects, involving academic researchers, physicians and applied scientists.

 

Rachel is a research and data science manager, passionate about algorithms, data and making products smart and natural to use.
She graduated with her Msc from Weizmann institute (cum laud) where her research focused on graph theory and optimization.

 

She has over 15 years of experience in industry roles, spanning from pure engineering applications to combination of algorithmic research and algorithmic implementation into production code, leading both engineering team and data science team.

Bio

Irit is a research manager specializing in Machine Learning and Speech Recognition, with 20 years’ experience in Israel’s high-tech Industry.
Her experience includes algorithm development and research in various domains, including speech and speaker recognition, data analysis, text analysis, classification and clustering methods and neural networks.


She is passionate about data of all types, and approaches any new data with respect.
She has led many R&D projects from conception to successful deployment at customers’ sites, and managed various collaborative research projects, involving academic researchers, physicians and applied scientists.

 

Rachel is a research and data science manager, passionate about algorithms, data and making products smart and natural to use.
She graduated with her Msc from Weizmann institute (cum laud) where her research focused on graph theory and optimization.

 

She has over 15 years of experience in industry roles, spanning from pure engineering applications to combination of algorithmic research and algorithmic implementation into production code, leading both engineering team and data science team.

Abstract

Coming soon

Abstract

Coming soon

Discussion Points

  • Data scientist role definitions – full stack data scientists vs. specialisations
  • Pure data science teams vs embedded teams
  • Data science reporting lines
  • Professional and personal development in embedded teams

Discussion Points

  • Data scientist role definitions – full stack data scientists vs. specialisations
  • Pure data science teams vs embedded teams
  • Data science reporting lines
  • Professional and personal development in embedded teams

Planned Agenda

Planned Agenda