As a relatively new role, “data guru” is a challenging job specification to draft for. Organisations are seeking highly-skilled and well-educated individuals to fulfil the position but, the truth is, the data scientist an organisation needs is not a guru, but a colleague.

Most organisations forget that recruiting the right talent is just as much about them as it is about the potential candidates. For example, does the organisation provide an interesting and successful environment for the data scientist to thrive in? Does it create new opportunities and positions for data scientists? Does it support its data scientists and allow them the freedom to work creatively?  

Understanding what data scientists look for is crucial when looking to recruit and retain the right data talent.

So, what makes a data scientist tick?

The fact of the matter is that the attrition rate for data scientists is very high. A recent poll by KDNuggets data scientists revealed that more than one in three expect to stay in their job for three years of less. There are a number of reasons that can lead to a data scientist deciding to hand in their notice, and often these things are in the organisation’s control – the company’s culture and technology available for the data scientists to use.

If the organisation doesn’t provide access to data and the tools necessary for data scientists to do their jobs well, it will lead to frustration. More importantly, these barriers make it difficult for data scientists to achieve their goals and perform to their best level, which understandably results in shorter tenures.  

Moreover, from a cultural perspective, many businesses aren’t quite up to speed with data. This starts with the C-suite: if senior management cannot see the value of a data-driven culture, then it will stifle efforts. A data scientist will soon feel under-appreciated and question the point of their analyses and recommendations if action isn’t being taken by the business.

Even if data is at the heart of the business, the data scientist is often left out of the decision-making process. Not only does this dissociate them from the hard work they have done, but it often leads to their work being misinterpreted, with the full benefits of the analyses being lost on the board.

What will draw a data scientist to work for a business?

1.The right challenge

Data scientists are often drawn to innovation – they want to be a part of it, to evoke it, and to drive it. First and foremost, you will attract data talent by ensuring that your organisation is pushing the boundaries of data analytics and use. Nothing is more engaging than a challenge, and data scientists want to be challenged by your company if they’re going to consider it as a place to work.

2. The right tools

This almost goes without saying. A good comparison is surgeons. You wouldn’t expect a heart surgeon to be able to carry out their job properly or effectively if they didn’t have the right tools or equipment available to them in the operating room. It’s the same for data scientists. Without the right tools in place, data professionals may only be working with partial, fragmented datasets or they may not have access to all the data they need, in order to gain the insights that will help to transform the business.

3. The right level of empowerment

With the right tools in place, people need to be given the space, time and trust to think and work creatively. Taking on-board their insights and actioning their suggestions will go a long way in making a data scientist feel appreciated and included in the company’s success.

4. The right training and development

Innovation is a constant within data analytics – from new tools and developments to learning from others’ methods and implementations. It is important your data scientists are continuously challenged and are learning new skills to keep up with this ever-developing market. Your organisation should open up a dialogue with your data professionals, so that you know what they want, what they are good at, and what they need from you. Only then can you help them develop themselves and grow into an integral role for the business.

Conclusion – It takes two to data science

The hiring process is not a one-way affair – while the organisations must make the decision to hire a data scientist based on their skills and experience, the data scientist must also decide whether the organisation is the right place for them to grow and develop their career.

As soon as organisations start realising this, then they can work on becoming a more attractive and exciting business to work for – providing the right challenges, tools, culture and environment for data scientists to thrive. In doing so, the pool of prospective data professionals that are applying to work for the business will inevitably increase, enabling them to hire the best people and to help the business grow and maintain data science success moving forwards.

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