Editorial
Data scientists come in many flavors. When you overlay industry knowledge considerations, it can be overwhelming (and challenging) to find individuals who best fit your needs.
Here are some questions that can help open your eyes to a broader range of candidates, or conversely narrow your needs down to what is truly important and help you avoid hiring the wrong candidates.
How Regulated Is Your Industry?
Many industries are highly regulated. Healthcare, insurance and financial services are all examples where an industry specialist has domain-specific knowledge that a new entrant to an industry will be hard pressed to match.
If you really need someone who can talk to regulators or understands proper secure data handling techniques, this dimension should drive your process.
Related Article: Data Scientists vs. BI Analyst: What's the Difference?
Does the Project Involve Structured or Unstructured Data?
Assuming the role doesn't entail strong industry-specific requirements, a good next question is: What are our business goals? And consequently, what data will this person work with to help solve them?
If the data is unstructured, then by definition, there are minimal business rules or knowledge imposed on the data. Here is where a generalist with strong machine learning skills can shine.
You are potentially going on a fishing expedition looking for that unknown insight. When fishing, an industry generalist with deep machine learning capabilities has two advantages: they have no preconceptions about how things are “meant to be” and they are expert at tuning systems to find insights in raw data.
Do You Have an Obvious Skills Gap You Need to Close?
You know your team. You know the types of data science your group is focused on. If you have a weak spot on your team, whether it be in data cleaning, analysis, modeling, general coding, or some other aspect of data science, closing the gap with a technical expert, rather than industry expert is probably the correct choice. There is an added benefit: the industry experts on your team will be freed up to work on the tasks they are passionate about and can provide greater marginal return on.
Related Article: 5 Communication Skills Every Data Scientist Needs
What Works Best for Your Type and Size of Organization?
In general, large organizations can more easily leverage individuals with deep, narrow skillsets and small organizations need people who can double up and serve multiple roles effectively.
How Quickly Do You Need a Solution?
If you need an answer tomorrow, a consultant may be a better choice than a full-time hire (full disclosure, I’m often a consultant). The right consultant brings a combination of deep industry expertise, with deep data science expertise they have already applied to your business needs, and a tool kit of already implemented solutions that could take years to develop internally.
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At the End of the Day …
Every situation and organization is unique. The breadth of data science in conjunction with your explicit needs means there is often more than one attractive candidate to meet your needs. Hopefully these questions help you identify the individuals best suited to assist in making your business thrive.
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