Inbal Budowski-Tal & Inbal Gilead

Delivering Certainty While Working With The Uncertain // Productization of Data Science Teams

EverCompliant

Inbal Gilead

Inbal
Budowski-Tal & Inbal Gilead

Delivering Certainty While Working With The Uncertain // Productization of Data Science Teams
EverCompliant
Inbal Gilead

Bio

Inbal Budowski-Tal is the Director of AI at EverCompliant, leading the Data Science team. Inbal received her Ph.D. from a joint program of the Technion and the University of Haifa in Computer Science and specializes in Machine Learning and Information Retrieval. Prior to EverCompliant, Inbal has worked as a data scientist at BiomX, a pharmaceutical startup, and at Microsoft.

 

Inbal Gilead is Director of Product at EverCompliant, a leader in the risk intelligence space, where she leads the entire Data products stack. Inbal is an experienced data and product professional, she had worked on data-driven products for over 12 years as a developer, analyst, and PM. Inbal holds an MBA from the Hebrew University, specializing in entrepreneurship &
strategic planning.

Bio

Inbal Budowski-Tal is the Director of AI at EverCompliant, leading the Data Science team. Inbal received her Ph.D. from a joint program of the Technion and the University of Haifa in Computer Science and specializes in Machine Learning and Information Retrieval. Prior to EverCompliant, Inbal has worked as a data scientist at BiomX, a pharmaceutical startup, and at Microsoft.

 

Inbal Gilead is Director of Product at EverCompliant, a leader in the risk intelligence space, where she leads the entire Data products stack. Inbal is an experienced data and product professional, she had worked on data-driven products for over 12 years as a developer, analyst, and PM. Inbal holds an MBA from the Hebrew University, specializing in entrepreneurship &
strategic planning.

Abstract

Solving business problems with data. Sounds trivial these days, no? Those of you who have tried taming data into valuable solutions and integrating them into your products, know the truth. When working on a business problem in a data science prism, potential solutions often require a significant research phase, during which the team can gain confidence as to whether a solution is viable and to gather information about it. During this phase, we focus on diminishing uncertainty so we can make data-driven decisions.

 

As Head of Data Science, I need the freedom to explore projects without committing to results; sometimes, it is impossible to know in advance whether we can solve a given business problem and how well the solution will perform. As a PM working with these teams, my goal is to challenge them with well-defined business problems & clear value definitions, while maintaining their focus to ensure the company can leverage their work promptly with minimum risk. We have developed a work methodology that helps us balancing these seemingly contradicting interests.

 

In this round-table, we will present our methodology, and show-case it on examples raised by the audience or by our own experience. We will discuss together how we can refine and adapt it to the project type and to the specific team/company.

Abstract

Solving business problems with data. Sounds trivial these days, no? Those of you who have tried taming data into valuable solutions and integrating them into your products, know the truth. When working on a business problem in a data science prism, potential solutions often require a significant research phase, during which the team can gain confidence as to whether a solution is viable and to gather information about it. During this phase, we focus on diminishing uncertainty so we can make data-driven decisions.

 

As Head of Data Science, I need the freedom to explore projects without committing to results; sometimes, it is impossible to know in advance whether we can solve a given business problem and how well the solution will perform. As a PM working with these teams, my goal is to challenge them with well-defined business problems & clear value definitions, while maintaining their focus to ensure the company can leverage their work promptly with minimum risk. We have developed a work methodology that helps us balancing these seemingly contradicting interests.

 

In this round-table, we will present our methodology, and show-case it on examples raised by the audience or by our own experience. We will discuss together how we can refine and adapt it to the project type and to the specific team/company.

Planned Agenda

Planned Agenda