Data science received a lot of attention in recent years. There are multiple definitions but in general, data science is the art of using complex statistical and computer science techniques on a set of data to identify patterns and shed light on the future.

It is a career that is still finding its footing, maybe because up until six years ago, there wasn’t any degree in data science. Indeed, when I was finishing my PhD (Bayesian statistics in astrophysics) at the University of Malta (UM) back in 2017, I hadn’t heard of “data science” before.

The question that I dreaded the most during my studies was, “what will I do next?” The job market seemed bleak, and when I sat down to search for job opportunities, I did not know what to search for. Throughout my studies, people’s aspirations about my future career were to end up in the world of academia or teaching, as these paths were deemed ‘appropriate’ for a woman to follow. The ‘advice’ given was that the tech world is still seen as a male-dominated field, and pursuing a career in data science will be an upward struggle.

Nonetheless, I was not wholly discouraged, and my family supported my choice to pursue sciences through and through. Once I started my first job as a data scientist with a private company, I realised how studying at the UM within the Faculty of Science and the Institute of Space Sciences and Astronomy prepared me to embark on my career journey in data science.

Topics such as matrices, linear algebra and vector analysis are the basic foundations of most machine-learning algorithms, including text prediction. Calculus explains how a data science model receives feedback to minimise errors and perform better.

All these subjects enable me to explain complex techniques to different people. Applying mathematics to a physics or astrophysics problem was paramount to acquiring the skillset of thinking outside the box. While business requirements vary across various industries, I had the right tools to tackle the problem head-on and build a career.

The main challenge for data scientists in Malta remains the lack of understanding of the subject by various sectors that guide employment. While things have improved (for example with new courses), I continue to advocate that further guidance about these careers is needed in educational institutions, and will continue encouraging students in pursuing their STEM studies and professions, including women who are thus far discouraged from pursuing a career in tech.

Deandra Cutajar is a Maltese data scientist.

Sound Bites

•        Various surveys identified that female graduates across different universities comprise roughly 55 per cent of graduates. Nonetheless, only  between 15 per cent to 22 per cent of all data science professionals are women. Gender pay gap, poor career growth, and gender bias in recruiting are some of the factors that influence whether women follow a career in data science or artificial intelligence.

•       Data is an art and not just a science. Building a great model is all well and good, but defending it against all odds requires communication and eye-catching visuals such as bar plots and scatter charts using interactive plotting tools.

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•        Data Science was initially used as an alternative term for computer science in 1974. Ten years later, C. F. Jeff Wu used it instead of statistics.

•        Artificial intelligence can predict the results of the Oscars with 90 per cent accuracy.

•        The World Economic Forum reported in 2021 that data science was identified as the skill with the largest skills gap.

•        Data scientists must also be great at storytelling. It is one of the most powerful skills a data scientist can learn.

•        Over 60 per cent of companies believe that it is not easy to fill data science roles because of severe talent shortages.

•        Poor quality of data costs the world’s financial organisations around 15 million dollars annually as estimated in 2017.

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