The data scientists embed their values, interests, and experiences into the data they handle, shaping outcomes in line.
Data Science is an excellent career choice for women at any stage in life — whether the women in data science are just starting out, considering a professional transition, or thinking of re-entering the workforce. Yet too few women make that choice.
What is Data Science?
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply actionable insights from data across a broad range of application domains.
In our data-driven world, companies are increasingly relying on data to make smarter business decisions, whether it be related to identifying what causes a business to lose or attract customers, personalizing healthcare recommendations, creating targeted advertisements, detecting fraud, or even things like finding the next group of world-class sports athletes or, for anyone who has ever used a dating app, finding love.
I. Why Is Data Science a Fantastic Career Choice for Women?
The first and foremost reasons that come to mind when discussing Data Science as a positive career choice are the widely heard promises of high pay and job growth. Indeed, looking at the data the national average salary for a data scientist in the United States is approximately US$114K, compared to a general population average of US$31K.
As for job growth, if the increase in available jobs since 2012 hasn’t impressed upon you the growing potential of this field, then consider what LinkedIn tells us in their 2020 Emerging Jobs Report, where data science is ranked #3 with a growth rate, after artificial intelligence specialist and robotics engineer:
II. The Field of Data Science Needs You:
It is not just that data science is a good choice for women. As the foundation of businesses’ decision-making process, as well as the basis of artificial intelligence, the field of data science in itself is in critical need of more women in data science representation as well.
III. Women’s Biggest Barriers and How to Overcome Them:
There is some degree of self-doubt, as it is common for women in this situation. Indeed, this doubt remains one of the biggest barriers still preventing or hindering many women in data science from entering the field. But it doesn’t have to be.
The most obstacles faced by women in data science are entirely perception-based. For once, it is not the world or society telling us that we cannot or should not do it. Instead, individual women are falling victims to the mistaken beliefs that they cannot make it in the tech industry, that they are not smart enough to code, or too old to learn, or any number of doubts rooted in their abilities and/or circumstances.
The reason why this high demand is particularly important for women is two-fold:
The first lies in the value of the skillset: As the pandemic has shown us, women face a higher likelihood of losing their jobs than men do. But this is not necessarily related to direct forms of discrimination. In many cases, it is simply because the nature of the job itself is less ‘valuable’ or less ‘essential’ than roles occupied by men.
Marketing, communications, education, retail are all today amongst the most female-dominated industries. Furthermore, a company’s administrative, HR and secretarial roles are also more likely to be occupied by women. As a result, when the pandemic it, women in these positions or fields were amongst the first affected.
However, the high value of a technical skillset can protect women in data science against such cuts. If you have experienced something similar, learning and switching to a data science position will certainly increase the protection of your job retention, whether in times of crisis or downsizing.
The second reason a high demand: is so important for women is that it limits the possibility of introducing the issue of gender into hiring decisions. With the number of companies looking to hire into analytical roles growing, women are significantly more likely to find a positive workplace and negotiate a competitive salary, as opposed to sticking to an unpleasant, or downright toxic environment for the sake of financial responsibilities and stability.
That is not to say that you may not face rejection when job hunting. Unfortunately, that is a reality we must all face one day or another, no matter the industry. What this does mean however is that in the event you are unhappy with your current work situation, as a skilled data scientist, you will not struggle nearly as much as in other fields to find another place of work more suitable to your values and needs.