Guest blog by The Data Lab MSc student, Warren Smith who studied an MSc Data Science for Business at Stirling University, 2019-20
The Data Lab MSc Programme is all about supporting our students on their way to becoming the data scientists of the future. Yes we provide 155 full fee scholarships annually for data science and AI courses across 13 Scottish Universities, but our programme is about more than that: we provide our students with a curated programme of networking and training that is designed to equip them with the wide-range of non-technical soft skills that are sought after by employers in our data community. Warren Smith, one of our The Data Lab MSc alumni, shares his views on this very topic.
Let Soft Skills flourish…
Being handy with Python, R, SQL, Machine Learning, Advanced Excel etc. is all swell, however the data scientist shall not live by Hard Skills alone. An adequate return on data science investment requires proficiency in a range of Soft Skills to boot. Not least of which are prowess in ‘problem solving’, ‘communication’, ‘teamwork’, and ‘business acumen’, to name a few of many.
The central importance of distinct Soft Skills in the appointment and performance of the able data scientist, is not well understood. A recent Masters’ dissertation project was carried out at the University of Stirling Management School, to research novel and germane aspects of the matter. The project modestly sought to identify fundamental Soft Skills in the recruitment of data scientists; to examine in contrast the perceptions of employers and completing data science students on elemental Soft Skills for data science dexterity and on Soft Skills fitness of graduate newcomers into data science employ; and to probe any workplace problems consequent upon lack.
A sequential mixed-methods approach elicited several useful findings. Comparing three data scientist vacancy regions: USA, London, and Scotland, all asked for the same top four Soft Skills in hiring. These are ‘grit & perseverance’, ‘teamwork’, ‘problem solving’ and ‘communication’, these varying in order between regions but always with ‘communication’ skills as number one.
Student and employer group evaluation on Soft Skills
An impressive harmony of perception between the two mentioned groups emerged on the importance to data science of almost all the Soft Skills considered, with no significant difference on seven of nine Soft Skills. Compared to the employers’ group, the students’ group evaluated ‘Leadership’ most significantly higher in gravity for data science. Both groups rated ‘Problem Solving’ as having the highest rank for data science accomplishment, with good agreement on the top four Soft Skills (‘Problem Solving’, ‘Critical Thinking’, ‘Attention to Detail’ and ‘Communication’).
On the issue of perceived Soft Skills readiness of completing students/ arriving graduates, the two groups differed significantly on eight of nine Soft Skills. The disparity between the two groups’ views was greatest on ‘Communication’. The employers’ group put forth a significantly dimmer view of how well university prepares the arriving ones on Soft Skills for data science competence. Imparting ‘Communication’ skills to students has the greatest lack, feel the employers.
A final case study interview with a prior data science graduate already transitioned into such employment, underlined the necessity of adequate ‘Communication’ skills, as well as a clear need for adaptability upon arrival and fitting in. The value of gaining real-world industry experience during university studies on data science was emphasized – this being a mirror of some of the free-text comments contributed within the earlier surveys.
Soft Skills are essential to success in data science, and major improvement to the situation of lack must include a lively and productive partnership between Academic Researchers, data science course designers, unitedly with the push and pull feedback of industry. A stumbling block to such an aligned collusion may well be the slow rate of change within universities.
Read next: Our Principal Data Scientist, Joanna McKenzie, gives her thoughts on soft skills: Creative data science and design thinking in data science projects