An AI framework for measuring the gap between universities and the labor market in the Circular Economy

Context

An Italian university, as the client, requested Technology Data Reply to create a framework based on artificial intelligence models in which university researchers could conduct their analyses regarding the national correlation in Italy between demand and supply in the field of Circular Economy, exploring the results automatically obtained from the intersection of job posting descriptions related to CE extracted from job posting platforms and the skills acquired by recent graduates through their university study programs (SUA sheets).

Scenario

In a university research context, the client has been studying for years the Circular Economy and the transformations of our society in order to adapt to the constant demand from the European Union for waste reduction and the application of the so-called 8 Rs.

To date, many studies have been conducted to understand how Italian universities are preparing new professionals for the job market to fill positions that require skills related to the Circular Economy and more generally to the world of ESG.

In this scenario, Technology Data Reply has been contacted to automate their research and data analysis to quickly and intuitively understand the gap between university offerings and job market demands.

Solution

The project consists of creating a data platform based on the architecture OCI (Oracle Cloud Infrastructure) where data from job postings is collected and analyzed automatically from the Glassdoor platform.

The goal is to identify those related to circular economy and correlate them with university curricula across the country, with provincial granularity. This solution automatically extracts key information from published job postings and simultaneously acquires Italian university curricula, merging the entire dataset into a data lake.

Therefore, modeling such data on a data warehouse and enriching it using Machine Learning and LLM models capable of classifying the extracted job postings, recognizing those related to the Circular Economy (CE), and extrapolating a score between training offers and CE job postings based on the degree of correlation between the professional profile formed by the university and the skills required by the job offer, on a territorial basis, so as to finally present these results in output on specific reports of a dashboard usable by users for their analyses.

Advantages

  • The team of researchers, using the interactive dashboard equipped with a map of the Italian territory, was thus able to navigate the results of the intersection between supply and demand, having an immediate snapshot of the situation in the country system Italy.

  • The solution in OCI allowed for an immediate scalability in granularizing the initial solution down to the provincial level, thus providing maximum visibility to analysts.

  • The solution in cloud not only lends itself to the extension related to data volumes and new types of data (see patents) but is also extendable to new analysis processes planned in the system.

  • Furthermore, this solution will become a data source important that will feed a lakehouse through which the resulting datasets of analysis will be shared with the scientific community and exposed as services to future private citizens who may benefit from it when looking for a job placement in their area of residence.

Contact us

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