If you’re data-obsessed, you may have considered becoming a data scientist. It’s a hot area. The demand for data science roles has surged recently in the US, with job openings more than doubling. At Adzuna, we’ve taken a look at how the data science field is evolving following the pandemic and as companies place more importance than ever on data fluency.
What is data science?
Data scientists are commonly employed by companies to find trends in data. In the role, they use programming code and other expert tools to create insights from data. Data scientists can explore past, current, and future data.
Data scientists are important as they can add large value to their companies. The role can help senior staff to make key, informed decisions based on trends, data, and facts. Data scientists can ensure that the products are best suited to their customers, for example. They can also identify opportunities for the company, as well as recruit the right talent.
Job titles in the data science sphere include data analyst, machine learning/ AI engineer, big data, and data scientist.
Since the pandemic, there has been a real change in the demand for data scientists. Before the pandemic, in March 2020, there were 4,806 vacancies for data scientists. To compare, the advertised vacancies for data scientists reached a huge 13,786 in March 2022. That’s an increase of 187% over two years.
Now, let’s look at the most common data science roles in a little more detail.
Head of data science
The head of data science oversees data management, creating data strategy, and improving data quality. Importantly, they also make sure that data is used to inform business decisions made at the executive level. Some companies are even creating ‘chief data officer’ roles as part of the executive team. The role requires experience as a data scientist, as well as knowledge of various programs. Additionally, some roles need a degree in data science or similar.
The change in advertised vacancies for head of data science roles has seen the biggest increase. In March 2022, there were 1,172 vacancies for head of data science roles. This was an increase of 331% from 2020 when there were just 272 vacancies.
Data analyst
Data analysts figure out how data can be used to answer questions, solve problems, identify trends, and make predictions. Excellent numerical and analytical skills are essential for data analyst roles. Degrees in relevant disciplines are often seen as desirable but not essential for every role.
The number of advertised vacancies for data analyst roles has also increased. The role has seen an increase of 112% in two years. In 2020, there were 6,623 vacancies for data analysts, compared to 14,047 vacancies in 2022.
Check out data analyst roles here.
Machine learning and AI
Advertised machine learning/AI engineer vacancies have seen huge increases in just two years. These job roles have seen an increase of 300% since the start of the pandemic. In March 2020, there were 1,811 job ads for machine learning/AI engineer roles. This is compared to 7,251 roles in 2022.
But what is a machine learning/AI engineer? The role involves researching, building, and designing artificial intelligence. These systems use huge data sets to generate and develop algorithms for learning and making predictions. This role generally requires a degree in subjects such as computer science, or data science. Programming and analytical skills are also required.
Jobs in artificial intelligence can be found here.
Big data specialists
With an increase of just 40%, vacancies for big data specialists have seen the smallest increase in job ads. In 2020, there were 2,294 advertised vacancies, compared to 3,200 in 2022.
Big data is simply any data set that is too large or complex to be processed by traditional software. This data can then be mined for information. Formal training in a related subject is required to become a big data specialist.
Explore jobs in big data.
Data engineer
While data scientists may code and train algorithms on data sets, data engineers help get the value from that data. Some companies even have two data engineers per every data scientist working on a project. With the help of better software and wider data knowledge, companies are paring down the number of tasks requiring the most experienced and skilled data scientists and moving some of those tasks to the remit of data engineers. Data scientists focus on problem solving, while data engineers build the infrastructure to help process, present and analyse the data.
This means the skills needed for data engineering are closer to full stack engineering, than data science.
Explore data engineer roles.
Wider investment in data fluency
With demand for data science specialists outstripping the supply of skilled talent, shortages can’t be fixed simply by hiring. Instead, companies are focusing on instilling data fluency from the top to the bottom of their organizations. This means that every department looks to data to help inform the decisions they are making. As a result, data-led decisions become the responsibility of the whole team rather than solely the data science team.
This is becoming easier with the use of less complicated platforms. For example, algorithms are being automated for those without coding knowledge. It also means data science skills are being deployed into wider business areas. Marketers may benefit from learning Python, rather than just excel. Similarly, finance teams may benefit from data visualization and modeling.
Many companies are also offering their staff opportunities to become more data fluent. Amazon has a ‘Machine Learning University’ for its developers, since opening the course up more widely. Airbnb also offers training to upskill its workforces through a ‘Data University’. Financial services company ING is another example, offering data science training to all their employees and encouraging what they call the ‘citizen data scientist’.
With such a growth in data science being seen, it’s a great time to enter the field. Some roles in IT are pretty lucrative, so the number of opportunities available will appeal to many. Make sure to check the job ads for any necessary qualifications before applying. If you don’t have the required skills and qualifications, look out for companies supporting their staff to become more data fluent.
If you’re looking to enter the data science field, why not search our millions of job vacancies here? Not sure how much you should be earning? Use out ValueMyResume tool to find your market value.
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