How and why to develop as a Data Scientist

How and why to develop as a Data Scientist

Continuing Professional Development (CPD) is a term that will already be familiar to many professionals. Your dentist, amongst many others, will be expected to show that she is keeping up with research and best practice.

Until recently, we heard little about this when placing data scientists or data engineers within businesses. However, that seems to be changing. Perhaps this is because of the increasing “professionalisation” of analytics. Either way, emphasising continual learning could be a very good thing for all involved.

Did you think it was just about studying hard at university to land that great first job? Are you hearing more about continuing to develop your skills and knowledge? The importance of this focus has been brought home to MBN during our conversations with 3 communities. In this post, I’ll share our perspective as a partner of all three.

One of the privileges of working on recruiting the right candidate for businesses is the opportunity to learn what they need. Our ongoing conversations, with a wide variety of data leaders, always give us insights.

Many people have spoken about the war for talent. With our strong links with universities and the wider analytics community, we also see this. With so many businesses waking up to their need of data scientists, demand can outstrip supply.

Many times, this means recruiting managers need to think outside the box. Their ideal wish list, of an experienced data scientist who is happy to be paid below the norm, may not be available. As we work with them, to help identify what is essential, learning is often key.

This chimes with the stories we hear from data scientists and their managers, years down the road. Those who settle well and who are most valued by their employer are those who keep on learning. It sounds like programming languages, data and business problems change. Those best able to adapt can cope with this reality.

For that reason, it is more important for data scientists (or data engineers) to be able to learn fast. Those who can quickly acquire new knowledge, or master new skills, thrive. CPD can really help them keep up-to-date with what may be needed next.

Only the other day, I saw a post on LinkedIn where a job applicant was complaining about all the programming languages he is expected to know. As he stated, he would need to spend many more years in university to graduate being fluent in all of them. Wiser employers realise it's best to look for candidates who can show their ability to learn new languages.

Some employers are also experiencing high turnover of data scientists, data engineers or analysts. After all the effort put into finding a viable candidate and bringing them up-to-speed on your business, this can be painful. Leaders I've talked with sometimes feel like resourcing their teams is a full-time job in itself.

However, there are positive stories too. We do also hear from candidates who are still happy with their employer and managers who are managing to retain a growing team.

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