A report, published by the Royal Society in 2019, claimed that in the five previous years demand for data scientists across industry had increased by 200 per cent. The report argued that this was the result of business and commerce, “crying out for professionals to unlock the potential of new technologies”.
John Salt, the CEO of OnlyDataJobs.com
If we were to look at the data science job market today, recent opportunities with the Royal Household, the England Rugby team and writing algorithms for a quantum computer tell us that demand hasn’t dwindled. But how many times have you attempted to recruit a data scientist? How many times have you interviewed one?
No matter your answer, I can guarantee that, irrespective of the industry or sector you work in, that number is going to increase exponentially. Across commerce, companies are increasing the number of data scientists they hire to help manage, analyse and interpret the numerous datasets the continual digitalisation of industry and commerce creates.
In 2022, Statistica published a piece of market research, which surveyed 403 individuals with a level of insight into the machine learning efforts of their companies across a random sampling of industries and machine learning maturity levels.
The research showed that, in the twelve months of 2020 to 2021, the percentage of surveyed organisations that employed 50 data scientists or more increased from 30 per cent to almost 60 per cent. On average, the number of data scientists employed in an organisation grew from 28 to 50.
However, that doesn’t necessarily mean that every business is ready to keep pace. Data scientists do a unique job, using tools that are rarely used outside their sector and, crucially, the way they view the outputs of their job is highly technical and complex.
Our task, as business owners, managers, and decision makers, is to understand those outputs and evaluate their suitability for the role in hand. Fortunately, there are steps you can take to ensure you get meaningful information out of the interview process when you begin hiring data scientists, which will be valuable for all levels of the business.
Listen for the anecdotes with actions
Do you really care whether the candidate prefers Snowflake or Splunk? Do you even know what that means? A much more relevant story would be one involving actionable organisational improvement that came as the result of the candidate’s work.
How did they improve an algorithm or model and what did that mean for the business, for instance? Did the work they do result in a more sellable or more sold product or service? Did it lead to staff retention, or even, in the case of the England Rugby, more effective team play?
Remember, having the right credentials is one thing, proving that the data scientist can use those credentials to create real, lasting business value is the true story recruiting companies want to hear.
Start with problems and solutions not numbers
The interviewee should be excited by data, but more importantly they should be excited by the problems they can solve using that data. Look for clear evidence of a solution orientated mindset. Ideally, the candidate will start with examples of the problems they have been called in to solve in past roles.
For instance, the job in the Royal Household was about producing and analysing project data on the wing-by-wing overhaul of the Palace’s infrastructure. So here, you would be looking for evidence that they understood and embraced the purpose of this project, not just that they are comfortable in Power BI and Azure.
Get busy on Google
If you don’t know your MLOps from your deep learning or your Azure from your AWS, you should probably do some initial research before the recruitment process begins, to ensure you understand the answers and the candidate’s requirements.
You don’t want to onboard your first data scientist and then discover they can’t do their job because they don’t have the right tools. Medium has a channel called Towards Data Science that would be a great starting point.
These three steps provide the perfect preparation for your next data science recruitment project, whether you need to recruit a quantum computer programmer, find the data scientist for a future season of The Crown, or help England land the Six Nations.
About the author: John Salt is the CEO of OnlyDataJobs.com, the UK’s largest data science only jobs board. An industry veteran, with time at TotalJobs Group, C-V Library, Reed Elsevier and Guardian Media, he’s an expert in internet marketplace, e-commerce and SaaS business models. He built Totaljobs Group sales channels and e-commerce from less than £2M to more than £70M, delivering profitable growth both there and at CV-Library.
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