Women in Data Science

Being a data scientist is the hottest job of the 21st century. Data science has become popular for the increasing amount of data we have to deal with in our lives. Like in many tech jobs, the share of women data scientists is rather low.

Data is generated from different sources like smart appliances, media streaming services, etc. To gain insights from data and turn raw data into valuable information, features from the fields of mathematics, statistics, and computer programming are fundamental. One could use scientific methods and algorithms to identify patterns in data. These patterns could contain valuable information and support the decision-making process and efficiency within organizations. For example, customer data from a customer’s age, income, past purchases, and browsing history could be useful to recommend products to customers. Or in the air travel industry, insights from data is used to make smart boarding decisions or decisions about food supply onboard without being wasteful.

Multiple studies indicate that only 20 to 26 percent of data scientists are women. To inspire women to become a data scientist, annual events such as the Global Women in Data Science Conference and the Women in Statistics and Data Science Conference are held in many cities around the world. In spring 2019, the Global Women in Data Science Conference takes place at Stanford University, California, and at the IT University of Copenhagen in Europe. At the conference, female speakers have been invited to give technical vision talks and there are opportunities to network. All genders are invited to join the conference. This year, Stanford University is organizing a Woman in Data Science Datathon, hosted by Kaggle (an online community for data scientists and machine learning), and the winners will be announced at the conference.

The field of data science continues to grow and all types of organizations within different industries need people to analyze the numbers and build models to make predictions. Data science, including many disciplines, is an incredibly broad field. A job in data science requires many hard skills, such as programming skills and statistical skills. Besides, a person has to be creative and is eager to deal with challenges. Women who have worked in the marketing, media, or PR industry have developed major creative and analytical skills. These fields do not directly relate to data science, but the skills could be very useful in data science.

More women in data science creates more diversity in the workplace. People with different backgrounds in teams lead to more creativity; it is beneficial because people with different backgrounds have different points of view and have different approaches to solving problems. Furthermore, women have excellent communication skills, are adaptable, and excel at asking the right questions.