Why you Should Consider a Data Science Career in Europe

Mark Taylor
Mar 25 · 5 min read

One of the most popular job roles in the world now, a data scientist is essentially someone who works with huge quantities of data possessed by organizations and analyzes it to extract useful insights that could offer valuable guidance to create useful business strategies. According to Investopedia, “the data scientist is often a storyteller presenting data insights to decision-makers in a way that is understandable and applicable to problem-solving.”

How has the role evolved over the years?

Data scientists started out as professionals engaged in data mining i.e. predicting outcomes by looking through large data sets to find anomalies, patterns, and correlations. With time, however, the data science industry has been tasked with problem-solving, by organizations across sectors.

Data intelligence is the power behind the business models of retail bigwigs such as Walmart as well as entertainment powerhouses like Netflix. Companies look to improve their operations by having data scientists collect, analyze, and interpret huge data volumes. They do this by developing statistical models that look at data and data sets in order to pull out patterns, trends, and relationships between variables. Be it for insights on consumer behavior or to know the business and operational risks, data science is critical.

What are the popular tools and methods used by data scientists in Europe?

In the course of their data science career, data scientists work on a number of languages. In Europe, Python is effectively a universally accepted data science tool, as seen by over 90% of surveyed professionals saying they use it regularly. Among the other options, Jupyter Notebooks are used by 65%, and SQL is chosen by 60%.

Among the methods popular in the data science industry, the top three most popular choices are logistic regression, neural networks, and random forests, with upwards of 50% of respondents claiming to use each of these three. The variety among tool preferences clearly falls short of that seen in chosen data science methods.

When it comes to languages, Python is far above every other modeling coding language, with about 70% of respondents preferring it as their primary choice. This represents a 10% growth from the previous year. The next three — R, SQL, and Java — together fall far short of even a third the claimed user base that Python has. Their user bases are estimated at 9% for R and 4% each for Java and SQL. Python is also the primary production coding language choice of 66% of respondents, again far ahead of other languages.

How are the job trends in data science?

With over 6,500 job openings, a median base salary of USD 107,801, and a job satisfaction rate of 4.0, ‘data scientist’ was at number 3 in the list of the most desired jobs in the US, according to Glassdoor. Even just a year ago, it was the top job choice, which points to the high desirability of a data science career. This high demand coupled with a shortage of suitably skilled professionals makes it difficult to hire data scientists, and holders of top data science certifications stand out in the race. Switzerland offers the highest mean salary at USD 113,428, with the next highest being Germany at USD 77,906 (converted at current exchange rates).

Once a company does manage to hire data scientists, it is also a task to retain them, given how there are many takers for their skill sets, and the consequent draw of high salaries. In Europe, the majority — 23% — look for an 11–15% hike in their pay packages, while 19% of them want 16–20% more money when changing jobs. For those looking to move their careers beyond Europe, top choices were the US, Germany, Switzerland, the UK, and France. And there is a variety of benefits that can be used to attract them, with equity stakes and free food becoming more popular than a year ago.

What should potential employers focus on?

In the data science industry, professionals looking to learn new skills on the job. This could be a major draw for them i.e. the opportunity to pick up and practice new skills. The industry is fast-paced — just 2% of respondents claimed to have been with their current employer for more than 10 years! — and there is much value in the chance to learn new technologies, which is what majorly determines how long a candidate will stay with an employer.

To improve their prospects, a candidate would do well to pick up one of the top data science certifications. A certification is a testament to the candidate possessing knowledge and competence with the latest skills, technologies, and practices in the industry. It also proves that the candidate is serious about a data science career and is looking to learn more and grow in the field, both of which are desirable attributes in someone to hire.

Mark Taylor

Written by

Professional data scientist, Data Enthusiast. #DataScience #BigData #AI #MachineLearning #Blockchain

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