The 3 Do's & Dont's Of Hiring Your First Data Scientist

Whether you are from a startup or a big corporation, every company today has one problem in common. At some point, there is a need to develop your own analytic capabilities so you can leverage your data efficiently. While outsourcing and getting help from consultants can be a great way to get things off the ground, eventually it does make sense to have the dedicated people in-house. And voila, you are searching for your first Data Scientist.

“Ok, this is a task for human resources. How is it different from hiring anyone else?”

There actually are a bunch of differences. Three to be exact. The key differences between hiring your first ‘data person’ and hiring for any other role are:

  1. Multiple areas of expertise - you want your first hire to be a great generalist, skilled not only technically (programming, databases, machine learning theory, statistics), but to be an excellent communicator and have a strong feel for the business side of things.

  2. Lack of reliable tests - while you can test reasonably well, whether a developer can code, testing Data Science skills is much more difficult. Especially in your first data hire, you are searching not only for the quality of execution of ideas. You want someone, who can generate new ideas and evaluate their feasibility as well.

  3. Don’t know what to search for - most of the resources out there are aimed at hiring people to an already existing Data Science / Analytics teams. While these are useful and can help you avoid some common mistakes, they also assume that there is someone who can reliably evaluate the candidates (aka has similar knowledge).

“Got it! So what can I do?”


  1. Hire for skills & mindset - in more mature tech teams with clearly defined roles and responsibilities, hiring people who are really good at a really specific thing, makes a lot of sense. Your first Data Scientist has a much harder role though. This person needs to have business domain knowledge, be a good generalist and have great self-activation. The ability to spot opportunities, prioritise and execute without the guidance from the top is really important to get your team started.

  2. Focus on people skills - let’s be honest here, when hiring for technical positions, it is not uncommon to compromise in the area of soft skills. While this might work in a lot of scenarios, it is a bad compromise to make for your first Data Scientist. This person will spend a lot of time collecting buy-in, explaining the findings and convincing people why the results matter to the business. Great communication is key here.

  3. Get help! - There are plenty of outsourcing opportunities for HR to pick from out there. However, replacing your own recruiter with an external one having the same skill set will not make a lot of difference. Make sure you are trusting someone, who has the skills and track record of hiring for a first-time Data Scientist.

Follow this advice and you will leverage your data in no time. Here at Knoyd, we have helped companies to get their Data Science teams off the ground and know how hard it is to do it properly. Get in touch if you are looking for help: