Spanish industry will need 90,000 data and AI professionals in the next 3 years

MADRID, Jan 28. (Portaltic/EP) –

The companies of Spanish industrial sector will require during the next three years the incorporation of more than 90,000 expert professionals in data and Artificial Intelligence (IA) to be able to carry out their projects and compete internationally.

The trend in the business sector is towards application of ‘big data’ technology and AI throughout the value chain of the industry, which means that companies will need to deploy experts in these fields in the near future.

During the next three years, only companies in the industrial sector will need more than 90,000 expert professionals in data and artificial intelligence to carry out their projects and compete internationally.

This has been pointed out in a IndesIA report, the Spanish artificial intelligence association for industry made up of eight Spanish companies: Repsol, Gestamp, Navantia, Técnicas Reunidas, Telefónica, Microsoft, Airbus and Ferrovial, with the support of the Basque Artificial Intelligence Center (BAIC), and Accenture.

IndesIA has also drawn up a training profile plan in which it has identified the twelve most necessary professional profiles for Spanish industrial companies.

These professions are: machine learning engineer, data architect, data engineer, IoT specialist, data scientist, data visualizer, data governance specialist, data owner, business data translator, data science citizen, industry 4.0 specialist and data analyst.

THE 12 DATA AND AI PROFESSIONAL PROFILES

The first of the profiles highlighted by IndesIA is that of machine learning engineer, an IT professional who focuses on researching, building, and designing self-executing AI systems to automate predictive models. In addition, they design and create AI algorithms capable of learning and making predictions.

In the case of data architect, it is a professional who is in charge of defining the data strategy, including the implementation and management of AI architectures, creating an integrated systems management to centralize, protect and maintain data sources. It requires knowledge of business intelligence platforms, architecture standards, as well as enterprise architecture and systems architecture.

Another of the most sought-after profiles is that of data engineer. It is responsible for designing, building, testing, and maintaining the data architecture (ie, large-scale processing databases) and data processes that enable most functions in the data world. The data engineer must be able to assemble a large volume of complex data, determine data storage needs, and build the infrastructure for optimal extraction, transformation, and loading of data from various sources.

This profile is different from data scientist, which is a data management specialist responsible for collecting, analyzing and interpreting large complex data sets to develop data-driven solutions and solve business challenges. Develop models (descriptive, predictive or prescriptive) and statistical learning tools for data analysis including machine learning algorithms.

IoT Specialist, on the other hand, is the profile of the expert professional in finding connectivity solutions between processes. Knows communication protocols, as well as the main components of a network and has knowledge of the software, basic programming skills and the ability to establish cybersecurity standards and to audit and make proposals for their assurance.

Another professional that the Spanish industry will demand is the data visualizer. It is 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. decisions.

the profile of the data governance specialist, also among the most sought after, is that of a professional who ensures the availability of data, its integrity, usability and its security. It facilitates the mechanisms and guidelines based on principles and best practices for the effective exercise of data governance.

Another job is data owner. This professional guarantees 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 maximum value in accordance with the company’s policies and with third parties. parts. Among its functions are defining the data quality rules, identifying and defining the aspects that may affect the data in terms of its treatment and the authorization of ingestion and distribution to use cases. You must also have legal and regulatory knowledge.

IndesIA has highlighted more profiles such as the business data translator. It is a professional who has both business and technical knowledge and who expresses 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.

Data Science Citizen, on the other hand, is the professional with in-depth knowledge of the organization who is capable of carrying out simple predictive analytical models. Due to his high knowledge of the business, he is able to present the results in the most appropriate way, so that decision-making is easier.

Another notable work is industry 4.0 specialist. This mainly industrial professional has skills that drive digital transformation and change management processes. He knows what the enabling technologies are in industry 4.0 and is capable of proposing solutions for each use case. In addition, he has a great ability to interpret the business and share it with the most technical teams.

The list closes with the profile of the data analyst. It is a professional who collects, processes and manages relevant data for the company. It is in charge of its statistical analysis with the aim of drawing conclusions that allow decision-making and value contribution, for which it is supported by business intelligence platforms and data analysis.

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