There are plenty of reasons why people move jobs in any industry or line of work, but in the world of big data there are key trends turning the heads of data scientists. Lukas Genever, a recruiter for technology specialists Churchill Frank, gives us his insight.
One thing I hear from data scientists on a daily basis is that they often feel that they are not being tested to their full potential. These individuals usually hold PhDs or MScs in STEM degrees where they have, in one way or another, spent years refining their mathematical ability and the increasing the number of advanced analysis techniques they can use in countless problems.
A trap I see a lot of companies falling into is that they hire data scientists without having the data they need to do the job properly. As a result, they end up cleaning data rather than finding value in it. These data scientists want to be tested, they want to be pushed and they want to be doing what they have studied for as they have a genuine interest and passion with data and numbers.
They also want to work with the latest technology. It’s incredibly important that you stay ahead of competitors by using the latest tools and techniques – otherwise in this fast-changing environment you could find yourself on the wrong track. I’ve found that Apache Spark, Scala and machine learning are becoming more prevalent, while artificial intelligence is very much on the horizon.
If there seems to be a real shift towards a certain technology, you should really consider adopting it or at least be open to the idea of upskilling your staff. And I know this isn’t possible for all businesses – and it’s not even necessarily the right decision – but it’s worth contemplating.
Naturally, salaries are becoming a big factor in why people are looking to leave their current roles. I’ve seen big jumps for mid-level data scientists – often bolstering their annual income by an extra £20K. Which is arguably over inflation, but businesses increasingly want to attract the best in the market as they know how important it is to build their data science teams.
Many businesses see it as an investment; a good data scientist will increase your income three-fold. And when the shortage of good data scientists comes to a climax you really could be paying through the roof – so make sure you’re staying competitive before it’s too late.
Sexy or challenging?
One important thing to consider is the vast range of data science work available. The Harvard Business Review dubbed data scientist “the sexiest job of the 21st century” – and part of the reason behind this is because every industry is looking at how they can use data to boost profits.
Most businesses know it’s important to grow their data capabilities; they’re now becoming increasingly aware of how important big data is to their future. What’s more, the amount of new start-ups monetising data in one way or another is so extensive that it’s becoming own market – so there are options out there and when there is so much choice it can turn heads.
Ultimately, if you’re not challenging your data scientists, applying the latest machine learning algorithms, or paying a fair wage, you could be in danger in losing your top performers. It seems to be a harsh reality, but that’s what it is: reality. I see it on a daily basis.
Lukas Genever, recruiter, Churchill Frank