Skip to main content
Data & AnalyticsData ScienceeBooksEmployerJobseeker

The Importance Of Representation In Data Science

By June 12, 2023November 29th, 2023No Comments2 min read

The importance of diverse representation in Data Science should not be underestimated.


A lack of diversity in Data Science has profound consequences; it increases the risk of bias in datasets and algorithms, which can result in inaccurate conclusions and poor policy decisions.

It also perpetuates gender inequality.

In April 2023, we hosted a webinar and were joined by four leaders for a rich discussion on the importance of representation in data; specifically, women in HealthTech data. The webinar was split into three parts, where our expert panelists explored topics such as bias in Data Science, the positive and negative effects of data on women’s health, and solutions for the problems caused by a lack of representation

This eBook covers the key insights shared by our four expert guests:

  1. Geetu Ambwani, VP of Data Science at Spring Health
  2. Christine Swisher, Chief Scientific Officer at Project Ronin
  3. Alison Greenberg, Co-Founder and CEO of Ruth Health
  4. Cokie Hu, VP of Strategy and Analytics at Sermo

Currently, much of women’s health is contingent on there being voices in the room asking the right questions. The aim of this eBook is to elevate these voices and catalyse continued discussions and action.

Check out our sneak peak & then download the full version below!

Like what you see? Download your copy below!

We’ve helped some of the most successful HealthTech startups grow.

— now it’s your turn.