Whether you are experienced or thinking about getting into Data science, in this guide you will find out:

• Which cities top the chart when it comes to the highest data scientist salary available?
• Do Data Scientists like working with startups?
• Do they want to stick to a job for more than a couple of years?
• What tools should you learn to get the highest data scientist salary?

We reveal all.

The Data Scientist is often a storyteller presenting data insights to decision-makers in a way that is understandable and applicable to problem-solving.  

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The role of Data Scientists has dramatically evolved over the last five years from mere data miners to complex problem solvers. From entertainment companies like Netflix to retail brands like Walmart – all have business models that now heavily rely on data intelligence.

Data Scientists collect, analyze, and interpret large volumes of data, in many cases, to improve a company’s operations. They develop statistical models that analyze data and detect patterns, trends, and relationships in data sets. This information is vital to predict consumer behavior or to identify business and operational risks. 

Data Scientist Salary – Is data scientist a high paying job?

For the year 2020, Glassdoor named Data Scientist as the third most desired job in the United States with more than 6500 openings and a median base data scientist salary of $107,801with a job satisfaction rate of 4.0.

When Glassdoor had named Data Scientist as the best job in the U.S, we published a scenario of Data Scientists’ jobs and salaries in Europe based on a report by Big Cloud.

Amidst this high demand of Data Scientists across the globe, it is not only difficult to hire Data Scientists, but also challenging to retain them.  Undoubtedly, salary is one of the major components when Data Scientists look at jobs and decide what is going to be their next big gig. A lot of experienced data scientists are increasingly freelancing to increase their salary.

Data scientist salary trends we picked up from a recent report by Big Cloud titled European Salary Report. This report delves into insights from over 1300 responses and 33 questions asked to professionals of all backgrounds, ages, and locations within the European region — the largest share of contributions being from Germany, France, UK, Netherlands, and Switzerland. 

Data Scientists prefer learning new skills on the job. Retain them!

Pay is a strong motivator although employees are willing to stay at their current company for longer – more so than before. This could be due to companies starting to understand the serious talent gap in the market and offering more competitive salaries to retain employees with new skills and increasing the overall average salary in the United States and Europe.

Comparing this to just 2% of employees staying with the same company for 10+ years, this data solidifies the ideology that Data Science is a fast-paced industry where Data Scientists and others in similar roles see value in learning new technologies and skills elsewhere. this comes as no surprise, as more companies recruit data scientist teams, salaries rise, and more specialist skills become sought after.

Python: The most popular modelling coding language for Data Scientists

70% of respondents said they use Python as their primary modelling coding language. This is a 10% increase from last year. A key skill to command at least an average data scientist salary. However, to go above an average salary more coding languages may be needed.

Broadly 9% use R, 4% use SQL, and 4% use Java. There were also 3% of respondents that said they don’t code.

In addition, 66% of respondents said their primary production coding language is also Python. These charts only highlight the top five primary modelling and production coding languages from the respondents. There were also 2% of use cases for C++ in modelling and 2% in Matlab. 

Most popular tools and methods used by Data Scientists

As high as 90% of participants chose Python as a tool they use regularly across Europe, which highlights just how universally accepted this data science tool is. Another 65% chose Jupyter notebooks and 60% chose SQL. When it came to Data Science methods, logistic regression, neural networks, and random forests were the top three most popular choices with roughly 56% of respondents claiming to use them.

Compared to a Data Scientists tool preferences, there is a much greater variety amongst their chosen data science methods. Other options in the survey (that didn’t make it to the top seven shown above) were 34% ensemble, 31% Bayesian techniques and 28% SVMs.

Expected Salary Increase by European Data Scientists

The Big Cloud survey asked its scientist respondents, ‘if you were moving jobs, what percentage salary increase do you think is realistic?’ A 23% majority expect to see an 11-15% increase in salary per year, with a further 19% expecting anywhere between 16-20%.

Upon comparing our 2019 results to the 2020 results, free food and equity/shares are more popular benefits now than they were than last year, with car/transport allowance and gym and leisure moving down the majority list instead.

If you are wondering where would a data scientist want to relocate for a new job? The top five places to relocate as a data scientist amongst European citizens were the United States, Germany, Switzerland, the UK, and France – the places with the highest data analytics salary on offer.

How much can you make as a data scientist?

Switzerland offers the highest salaries for Data Scientists

Here is a look at salaries in different cities in Europe (including the UK for now)- Switzerland leading the way!

Data Science salary in the United States

If you are on either coast this makes a difference, according to indeed the average data science salary is $123,785 and according to glassdoor its $113,436.

Entry-level can range the widest from $50,000 to $90,000. this probably depends on your prior background and education in your career and of course, location.

Seeing that the data analytics industry is young, its not surprising to see professionals more active in moving employers often as anyone with experience becomes far more valuable to companies and can reach manager status quickly.

Data Scientists are more than willing to work with startups

Across all industries in Europe, 68% of people do not currently work in start-ups. Despite this, the data science market remains open-minded, with 83% saying they would consider joining one in the future.

The respondents that currently work in start-up industries are primarily Technology/IT and Consulting (37%). Respondents from these two industries are also respectively the majority that would consider working for a start-up in the future (38%).

Which industry do Data scientists work in?

Consulting was the number one spot in the O’Reilly salary survey, followed by software and banking. No surprises there as these companies have the resources and huge amounts of data to go through. We fully expect data in insurance to be one of the biggest growth areas in 2021.

Final thoughts on a data scientist salary in 2020

Python is the most used although to increase your salary data science skills should continually be enhanced, especially start-ups looking for more rounded skills with SQL and Spark, for example, will only add to boost a data scientists salary.

O’Reilly’s Data Science Survey found that learning D3, visualization library in javascript can boost a salary by $8,000 a year.

SQL, Excel, R and Python are the most commonly used tools although we would suggest learning another to make your resume really stand out.

Lastly, familiarity and experience with cloud computing will also boost salaries, with respondents who use Amazon Elastic Mapreduce getting a boost of about $6,000 in their salaries.

Big data in 2020 is still growing with lots of companies still to recruit we think scientist salaries will continue to rise, and the remote opportunities will also grow as companies compete for experience, skills and need to widen their job search to all geographies to recruit this in-demand skill set.

Disclaimer: The content of this article is from Data Science Salary Report 2020 Europe by Big Cloud & O’Reilly Data Science Salary Survey

Here is what a recent report says about job opportunities for Data Scientists across Europe including salaries and benefits, job motivations, programming languages used, tech skills and what people want most from their work.

Glassdoor names “Data Scientist” as the best job in the United States for 2019 and LinkedIn ranks it number one among the top 10. Topping the list for four years in a row,  Data Scientist has a job score of 4.7, job satisfaction rating of 4.3 with 6,510 open positions paying a median base salary of $108,000 in the U.S. But what is the scenario for Data Scientists in Europe? What is the demand and supply? Which countries in EU are the best destinations for Data Scientists and what salaries can they expect? A recent report titled Data Science Salary Report 2019 Europe by Big Cloud  answers some of these critical questions.  

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First, a little flashback: According to a report by the European Commission in 2017, the number of data workers in Europe will increase up to 10.43 million, with a compound average growth rate of 14.1% by 2020. The EU forecasted to face a data skills gap corresponding to 769,000 unfilled positions by 2020 in the baseline scenario and being concentrated in particular in the large Member States (especially Germany and France). The European Commission suggests that 100,000 new data-related jobs will be created in Europe by 2020. Hence, there are huge opportunities to be deployed from the digitalisation of European industries.

Now, let’s dive into some of the key findings of the report by Big Cloud. The most popular countries to take part in the survey have been Germany, United Kingdom, France, Netherlands, Spain, Italy, and Switzerland. “The majority of respondents have been Data Scientists, however, we^’ve seen a great number of Machine Learning Engineers, Data Architects, Researchers and C-Level professionals taking part too which has offered a broad scope of the European Data Science market at all levels,” says Matt Reaney, Founder and CEO, Big Cloud, a company based in Manchester’s Northern Quarter which deals with Data Science and AI recruitment.

The report looks at the overarching trends of the market including salaries and benefits, job motivations, programming languages used, tech skills and what people want most from their work. Here is a snapshot:

Data Scientists : Lack of Supply , More in Demand

Interestingly, 58% of the respondents in the report have been at their present company for one year or less. Similar to 2017, this highlights the lack of supply of Data Science talent, compared to the heightened demand. It’s also worth noting that this shows how much people move about within Data Science roles. It’s not an industry where people stay in the same job for very long. Data Science roles are often very project oriented, and we find that Data Scientists like to move to other companies where they can learn new technologies and skills.

Data Scientists like working in Startups

Out of all industries included in the survey, 71% are not startups, which shows an established Data Science market in European countries. There is, however, still an exciting start-up scene, especially in cities like London, Paris and Berlin. A further 71% of whom are not already working in a startup, said they would consider joining one in the future, with only 8% saying they wouldn’t be interested in doing so, and 21% being undecided.

Switzerland offers highest Data Scientist salaries

The highest data science salaries can be found in Switzerland, with an average annual data science salary of  € 115,475, followed by the Netherlands, at €68,880 . Below is a segregation:

Python is the top production coding language for Data Scientists

Below are the five most popular primary modelling coding languages selected by respondents, with 59% using Python. Similarly, Python has come out on top as the most popular production coding language, with C++ 2nd with just under 20% of respondents using this for production coding, but there is quite a large gap between them. There is an even spread of hours spent coding, which could be indicative of the broad range of seniority and experience levels of respondents. The higher paying positions usually consist of less coding hours.

Data Scientists seek meaningful jobs

Between 2017 and 2018, there has not been a vast change in respondents happiness in their current job, in 2017,the report recorded that 65% of people were happy in their current job, which has this year reduced to 62%. Moreover, 68% said they would find it easy to find a new job, which is telling of the demand vs supply Data Science market. It’s also an indicator of the confidence Data Science professionals have in the hiring market. Much like 2017, the top reason to find a new job is higher earning potential. The desire to work on more meaningful projects has overtaken the desire for better work-life balance, most likely indicating the shift in companies beginning to be more accommodating with flexible and remote working.

“In 2017, we saw a reflection of the current hot topics of the day that people wanted to work on – such as fake news. This year, however, we’ve seen an increase in people wanting to use Machine Learning to combat things like climate change – which is a pressing issue of today. Similarly, we’ve seen an increase in people wanting to use Machine Learning in police investigations and counter-terrorism, which could be reflective of the increase of such events in Europe in recent years,” mentions the report.

One overarching trend is for sure, and that is that Data Science professionals want to work on projects that have a positive impact on society.

Final Thoughts

One of the reports by Dataiku rightly mentions that Data scientists are in demand, which necessarily means they are difficult to keep around – after all, they can easily find a position elsewhere. But it’s also a question of happiness: if data scientists were satisfied with the work they do, even if they could find a job elsewhere, they might be less inclined. And since the position is relatively new, many companies don’t really know what to do to retain people in these important, cutting-edge roles. Clearly the industry is populated by winners and losers, companies that know how to best use their employees (including their data scientists) and those that don’t. But it’s not just up to the company – there’s work to be done on the side of data scientists as well, making sure that they market themselves to make their job and the work they do indispensable and visible to others to continue to grow and be able to take on more exciting projects for ever-increasing job satisfaction.

Disclaimer: The content of this article is from Data Science Salary Report 2019 Europe by Big Cloud