Data Scientist or Data Science Team
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Many businesses struggle to recruit the talent they need. We see this particularly in fields like Data Science, where such skills are in demand to help business growth.
Although our track record is strong in helping our clients fill such roles, still the demand grows.
Partly for that reason, we also spend time talking with data science leaders about what they are seeking to achieve and how they are making progress. From these conversations, an interesting theme has emerged. Several top performing teams and their leaders appear to have taken an approach to securing the skills they need that we think is worth sharing. After all, it’s people like you, using data science to make a difference in their businesses who are the real experts (not us recruiters).
Difficult to find the ideal individual
As we’ve shared before, a Data Scientist is a challenging role. Such a demanding mix of skills is required. From high-end technical expertise (in data languages & machine learning), through strong numerate skills (in maths and stats) to the business skills to apply their learning (e.g. communication & influencing). It’s perhaps not a surprise, then, that recruiting managers can struggle to find such an ideal candidate.
But, is the answer to keep seeking that perfectly rounded Data Scientist? Is success really about one individual? We’ve seen a few clients who have proved another approach can work better. By putting the focus on the team, not just the individual, they more easily recruit teams that comprise all the skills they need.
Swiss Army Knives
By way of analogy, consider the famous Swiss Army Knife. It’s one of those aspirational items you hear about from childhood, especially if you’re an outdoors type. Since the first such multi-purpose pocket knives was produced for the Swiss Army in 1891, it has set the standard for both quality and having all the tools you could need in one ‘knife’. However, none of those individual tools is perfection for the job to be done. A bigger screwdriver, scissors, corkscrew etc., would be better at doing any individual job. The brilliance of the product, is to pack so many different functions into one small portable item, which you can safely keep in your pocket.
I’m sure you can see where this is going…
In many areas of business and sports, leaders have seen the power of assembling high-performing teams, not just ’star player’ individuals. One of the reasons for the success of psychographic screening tools, like Belbin Team Roles, has been to help those assembling teams think how individuals will complement each other to form stronger teams. But many leaders have shown this can apply not only to personalities & character strengths, but also to pooling technical skills.
So, what if you stepped back a moment from that Data Scientist role you want to fill. Are they part of a team? What does that team look like?
Since Google first coined the job title ‘Data Scientist’, a range of associated job titles have started to emerge on the jobs market. Data Engineer, Data Architect, Lead Scientist, Data Programmer are all starting to reveal the need for supporting roles. Is it possible that your business requirement, even your data science requirement, could be best spread across a team rather than one specialist?
The success of teams
We’ve seen businesses with large data science functions succeed in recruiting individuals who are strong in only part of the ideal job spec. For example, recruiting skilled coders to complement existing statisticians. Adding individuals with strong business analysis and communication skills to more technical teams, or artistic data visualizers to teams with the other data skills. All these approaches have proven to strengthen their teams.
As Aristotle said, ‘the whole is greater than the sum of its parts’. That is the brilliance we have seen in this approach. It appears, at least from where we are sitting, that those businesses who assemble such multi-skilled teams achieve more from that synergy. Quite often they appear to make more difference in their businesses, compared to those who hired the most highly skilled individual data scientists.
Could you think differently?
Data Scientist or Data Science team? The answer depends on the needs of your business and how much you can afford to invest to grow. But from what we’ve seen, it’s well worth remembering that good old Swiss Army Knife.