Why Women in Engineering should consider Data Science as a career

There are many reports and data collected about the shortage of women in Engineering but there is a specific one that I would like to highlight here:

This data is very surprising when it is a very well-known fact that there is a shortage of engineers or STEM graduates in the UK. In the last few years there has been an effort to drive more young people into choosing Engineering as their career and despite all this effort only 12.37% of all engineers are women. So, there are few women going into the profession and then fewer remaining within that profession.

There are many reasons that could explain this trend but it is worth to mention, like in many other professions, a large proportion of women still assume the role of the primary carer for their children and often find it challenging to ‘juggle’ responsibilities both at work and at home, choosing to move into a career in which it is easier to find a better work-life balance or not to work at all .

Data Science is a growing profession applied in many different fields where companies struggle to manage their data. The need to make informed decisions and spot patterns based on the data collected will open positions to data scientists in many companies. We can easily think of examples within the financial sector, retail industry, marketing , social media and politics to mention some where data scientist have used their skills

Data is generated constantly everywhere and so is in manufacturing plants, processing plants, renewal energy, automotive industry, etc. Engineers have been making data driven decisions on a daily basis as part of their jobs but the amount of data piling up is overwhelming and they often lack the skills to manage it. In the future a data scientist will be working alongside teams of engineers to automating and refine even more their processes in this constant changing environments.

The set of skills a good data scientist should manage is vast but a very important skill he or in this case she should posses is to be able to understand and correctly interpret the question that it needs to be solved and then, consequently interpret the results to their target audience, in this case other engineers. Having a common education background should facilitate this communication and mutual understanding. Data scientist from different background might find this data challenging and maybe missed some important information that it would have been picked up by an engineer.

The raw material of data scientist is “data” and it can be access remotely once proper channels to gather this data have been stablished allowing more flexible working hours for women.

The earning potential as a data scientist is similar or even higher than their engineering peers making it an attractive career path and if money doesn’t drive you there is nothing better than working in a field that you love!

The skills needed to start in this path would take a few months and then years of practice to master them. Most of those skills are available online and you can find the information on many blogs available about this transition into data science.

Here they are some examples:

And here is an example of how data science is transforming the automotive industry with Machine Learning which as it has happened in the past it will open the path to other manufacturing industries to follow the lead.

I hope this short story has planted a seed of thought in your mind and it has open a new window of opportunities to consider data science as a career and explore it further.

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