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We interviewed Alex Rutter, a specialist data-science recruiter in London on why data scientists leave their jobs as part of a three-part series. In the series of articles, we look into how data scientists can ensure they make the right move, what clients can do to retain their talent, and ultimately why turnover is so high in the data science space.

You may be surprised to hear that the average tenure of a Data Science professional in London is only 1.2 years (LinkedIn Insights, 2020).

Despite Covid related uncertainty, I have found that the underlying motivations and drivers for Data Scientists have remained constant.

Following hundreds of interviews over 2020 here are the top 6 reasons Data Scientists look for new jobs.

Lack of Training & Opportunities to Upskill

The first reason for looking to leave is that Data Scientists feel they are not getting enough training and are not being given enough opportunities to upskill in their current roles. This is common at all levels of seniority, with a high percentage of seniors feeling like they are plateauing having completed everything they were brought in to do.

In 2020, the highest growth areas for learning in Data Science are Cloud-Based (AWS, Azure, and GCP), Machine Learning, and Apps (Docker, Git, Shiny) (R-Bloggers, 2019). Personally, I have found that Data Scientists want to work with the latest in AI (e.g. advanced automation), Cloud-Based, NLP, deep learning, and conversational analytics technologies. As this is such a fast-moving market, I am sure there will be new technologies to take a podium place soon!

I have found that it's usually a lack of time, funding, guidance, and resources that prevent Data Scientists from learning and upskilling on the job.

Progression Opportunities

Limited progression opportunity is another crucial reason Data Scientists want to leave (not unlike other professions). It is rare to speak with a Data Science professional who does not want to work their way up to a more senior post throughout their career. By not upskilling staff, you are limiting opportunities to develop and progress to the more senior roles so many desire and which I guarantee they will leave to find.

Similarly, Data Scientists want more responsibilities – leadership, autonomy, management, influence, strategy, decision making – that come with progression, which is almost impossible when there is a lack of support, lack of infrastructure, and limited upskilling resources.

Not What it Says on the Tin – Expectations

The issue is prevalent across a multitude of roles and industries, but in my experience, quite often in Data Science (synonymous terms and job titles do not help!). The vast number of data scientists looking to move in the first year in a role is nearly always down to being oversold. Often due to the struggle businesses face when competing for the best talent candidates are sold a dream role, then 4-12 months still have not come close to what was promised.

Often Data Scientists are told they will make a significant impact on the business but ultimately do not. Again, this could be down to false advertisements and promises or unrealistic expectations on the Data Scientists part…95% of the job is not flashy headlines, it is the hard graft and small incremental gains that goes on behind the scenes.

The hype around Data Science does not help either, especially with the media focus on advances in Artificial Intelligence and other cutting-edge technologies which creates a skewed perspective for some Data Scientists of what they will be doing in a role.

Internal Business Battles – Politics

Almost half of the people I speak with say that bureaucracy and internal politics are the most significant challenges they face as a Data Scientist. I believe this is down to the immaturity of Data Science in comparison to other business departments, along with archaic decision-making processes. These issues can quite quickly create a toxic culture that takes focus away from the business's end goal and can increase staff attrition.

Additionally, with the hype around Data & Analytics in modern times, Senior management look for short term wins by building out a Data function when no one understands what Data Scientists do and why they do it. Especially with Senior Data Scientists, when there is no direction or roadmap in place, not many projects will come up, leading to your Data Scientists leaving. Moreover, Senior's place a lot more focus on Data being put at the center of the business, aligning with business goals.

Lack of Support & Community

I often get told how individuals in certain businesses get no support from senior management. This includes not being given resources or the right tool, and as you can imagine, it is too tiring for Data Scientists to constantly battle and petition all the time. As illustrated in the WiD Conference Survey (2019), over a quarter (29%) of respondents named a lack of support from managers and leaders as a reason for leaving.

Berinato's Harvard Business Review similarly discussed 'lack of management/financial support', 'results not used by decision-makers' and 'explaining Data science to others', as having a massive impact on the frustration felt by Data Scientists.

Moreover, at least half of the people I speak with say they have no internal Data Science community where they can share knowledge and learn. This lack of support can come from adjacent departments, too, as the Senior people I have spoken with say that working in siloed teams makes it almost impossible to deliver real business value.

Salary & Compensation

This reason occurs in any job, but due to the 'desirable' status of Data Science the capital-rich, tech giants are willing to offer salaries you would rarely turn down. These tech companies are monopolising their industries with infinite amounts of capital, allowing them to take a pick from anyone with the skills they desire.

However, this is having a ripple effect on the market by creating distorted salary expectations. The tech giants are paying well above the market rate, which most smaller companies cannot do, making it harder for them to retain the best talent.

There is no question that salary is one of the significant components Data Scientists consider when looking at jobs and deciding what is next. Evidently, around 65% of Data Scientist will get a 10-20% salary increase when changing jobs. Whereas, if they stay in the same position, this figure is only 2-4% each year (Burtch, 2019).

So, how can clients keep Data Scientists happy and retain them, we'll be sharing this in our next article but to ensure you don't miss out connect with Alex on LinkedIn.

If you are hiring data scientists and keen to speak with a specialist data-science recruiter, then do contact Alex on 0203 3974565.

Consortia is a niche tech recruiter focussed on Product, Developer, and Data and are recognised as one of Europe's leading Data Science recruitment agencies.

If you are considering your next move, check out our latest data scientist jobs in London or to save time, get in touch to discuss your perfect fit.

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