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The 12 professional profiles that the Spanish industry will demand the most

During the next 3 years, companies in the industrial sector alone will need more than 90,000 professionals who are experts in data and artificial intelligence.


The trend in the business sector is directed at the application of big data technology and artificial intelligence (AI) throughout the industry value chain. This means that, over the next few years, companies will need to have among their teams expert professionals capable of dealing with matters related to these two technologies without difficulty.

In this sense, from IndesIA, the Spanish artificial intelligence association for industry, made up of eight large Spanish companies, Repsol, Gestamp, Navantia, Técnicas Reunidas, Telefónica, Microsoft, Airbus and Ferrovial, and which has the support of Basque Artificial Intelligence Center (BAIC), and Accenture, point out that during the next 3 years, only companies in the sector will need more than 90,000 professionals who are experts in data and artificial intelligence to be able to carry out their projects, boost the country's economy and be able to compete with other organizations international.

"The lack of qualified personnel is an obstacle to the growth of companies and, therefore, to economic recovery," explains Valero Marín, president of IndesIA. For this reason, he indicates that “one of the main objectives that we set for ourselves as an association is to promote the transformation of employment towards professions focused on new technologies. It is about reducing the gap between the training of the disciplines called STEM (science, technology, engineering and mathematics) and the needs of companies. But we also want to promote the creation of new highly qualified jobs and higher quality employment. Likewise, attract and retain technological talent in Spain”.

The 12 most demanded profiles
Thanks to the work that IndesIA carries out hand in hand with the main Spanish industrial companies, it is possible to know which profiles will be the most requested in the sector in the short and medium term. Thus, the association's experts have drawn up a Training Profiles Plan in which they have identified what these professions will be and considering that the 12 most necessary will be *Automatic Learning Engineer, Data Architect, Data, IoT Specialist, Data Scientist, Data Visualizer, Data Governance Specialist, Data Owner, Business Data Translator, Data Science Citizen, Specialist in industry 4.0, Data Analyst.

This plan also details the capabilities and skills to a greater or lesser extent, they must have and that have to do with data analytics and statistics, the implementation of analytical models and platforms, programming, development of methodologies and processes, the creation of business intelligence platforms, knowledge of data engineering, business architecture, data quality and governance, data management and visualization, security and, in short, aspects related to technology IoT.

As explained by the president of IndesIA, the Training Profiles Plan has a double objective. On the one hand, knowing what talent is required, but on the other, defining the roles they will occupy within the companies and specifying their functions and capabilities, unifying the criteria that each organization has regarding these professions. “The novelty of these jobs means that sometimes we find that the profiles are not well defined in terms of the knowledge they must have and the work they are going to do. To the point that, sometimes, it is difficult to understand what is the difference between some professionals and others. Thanks to this unification of criteria, it will also be easier to offer training that coincides with subsequent job performance or to recycle the skills of professionals who are already part of the companies,” he warns.

On the other hand, it also explains that both the list of these professionals and their skills are not static or closed descriptions, since the advancement of technology itself will cause their skills to evolve and the creation of new positions. In addition, he comments that other types of non-technical profiles such as humanists, specialists in law, design... etc., will also have to adapt their knowledge to data and artificial intelligence issues.

Agreements with universities and other training centers
To alleviate the shortage of expert profiles in these technologies and achieve the long-term transformation of the country, it is also necessary to bet on training and education. According to a report by OdiseIA and Humantrends, "The Barometer of ethical artificial intelligence in Spain", in 2020 there were 56 degrees and 14 master's degrees in public universities with artificial intelligence subjects. Although this number is increasing, the figure is still low for the transformation that is needed.

To commit on the training of people in IndesIA they plan to work together with public and private educational institutions with the aim of defining training itineraries with which to cover both the general knowledge that employees of the industrial sector must have. IndesIA will provide knowledge so that university centers can respond to the professional needs of companies and work on curricular adaptations to bring students closer to the reality of the world of work.

Gender gap in new technologies
According to data from the Government of Spain, the digital gender gap has been progressively reduced in Spain. But in advanced skills, we are still below other European countries. On the other hand, there is a large difference between the sexes in the number of graduates in STEM studies. According to the president of IndesIA, it is important to deal with the reduction of this gap and put specific actions to work in that direction.
“If women are not encouraged to access and want to be trained in aspects related to these new technologies, and at the same time the demand for these profiles continues to expand, the digital gender gap runs the risk of widening. In addition, the industry will be losing such a necessary and valuable talent as the female talent”, he adds.

Professional recycling
Another consequence of the lack of technological talent is that companies are realizing that their future cannot depend only on the youngest talent, junior professionals who are already joining them or will join them in the coming years and in which Training in subjects such as big data or artificial intelligence is already being promoted.

Thus, in IndesIA they also highlight the need to retrain workers with more experience with digital skills. This is how they intend to make it easier for companies to establish internal training programs. Something that, in Valero Marín's opinion, must be done for several reasons, "on the one hand to have the talent they need and on the other, so as not to be left with an obsolete workforce and senior workers who do not have the digital skills and competencies that the market demands”.

* Description of profiles:
Machine Learning Engineer. IT professional who focuses on researching, building and designing self-executing artificial intelligence (AI) systems to automate predictive models. In addition, they design and create AI algorithms capable of learning and making predictions. They have to operationalize and optimize the models and algorithms developed.

Data Architect. Professional who is in charge of defining the data strategy, including the implementation and management of artificial intelligence (AI) architectures, creating an integrated systems management to centralize, protect and maintain data sources. He requires extensive knowledge in business intelligence platforms, architecture standards, as well as enterprise architecture and systems architecture.

Data Engineer. Professional responsible for designing, building, testing, and maintaining data architecture (i.e., large-scale processing databases) and data processes that enable most functions in the data world, for which it will be required Extensive knowledge of relational databases. As well as being able to assemble a large volume of complex data, meeting non-functional and functional business requirements as well as determining data storage needs. It will also be his responsibility to build the necessary infrastructure for the optimal extraction, transformation and loading of data from various sources, with the aim of achieving high scalability, efficient data delivery in automatic processes.

IoT specialist. Expert professional in finding connectivity solutions between processes. He knows communication protocols, as well as the main components of a network and has knowledge about the software that connects the IT world with the OT world. His basic programming skills allow him to make the connection between these two worlds. In addition, he can establish cybersecurity standards and is capable of auditing and making proposals for his assurance.

Data Scientist. Professional specialist in data management who is responsible for collecting, analyzing and interpreting large complex data sets to develop data-driven solutions and solve difficult business challenges. He will develop models (descriptive, predictive or prescriptive) and statistical learning tools for data analysis including machine learning algorithms.

Data Viewer. Professional responsible for the creation and visual editing of the content, performing the extraction, transformation and loading of the data set into maps or graphs, dashboards or more visual reports that serve the rest of the organization in their interpretation and allow decision making.

Data Governance Specialist. Professional specialist who will ensure the availability of the data, its integrity, usability and its security. It will facilitate the mechanisms and guidelines based on principles and best practices for the effective exercise of data governance. It will be in charge of the transversal coordination of businesses and functions for the exploitation and democratization of data.

Data Owner. Specialist professional who will guarantee the quality and consistency of the data, ensuring that they are suitable for use within the scope of the organization's needs in the most flexible and effective way possible to achieve their maximum value in accordance with company policies and with third parties. Its functions include: defining data quality rules. Identify and define the different aspects that can affect the data in terms of their treatment and the authorization of data intake and distribution to use cases. You must also have legal and regulatory knowledge that affects the processing of data.

Translator of Business Data. Professional who has sufficient knowledge in both business and technology to express the needs of the organization in a language that is valid so that the data scientist can make the models or algorithms that meet the requirements.

Citizen of Data Science. Professional with in-depth knowledge of the organization's business, who is capable of performing simple predictive analytical models. Due to her high knowledge of the business, she is able to present the results in the most appropriate way, so that decision-making is easier.

Industry 4.0 specialist. Mainly industrial professional, with skills that drive digital transformation and change management processes. She knows what the enabling technologies are in industry 4.0 and is capable of proposing solutions (at a high level) for each use case. On the other hand, it is a profile with well-developed social skills, which guarantee their ability to record customer requirements completely and correctly, helping to identify problems or improvements in industrial plants. In addition, he has a great ability to interpret the business and share it with the most technical teams (Big Data, software development, networks, etc.).

Data Analyst. Professional with great knowledge of the business who collects, processes and manages relevant data for the company, being in charge of its statistical analysis with the aim of drawing conclusions that allow decision-making and value contribution. They rely on business intelligence platforms and all their capabilities for data analysis.