Abstract: Despite technological advances in matching people with jobs, labor market is still highly inefficient: millions of jobs stay unfilled, while a comparable number of professionals are trapped in jobs they do not enjoy. Finding the right development path for a person or an organization requires an understanding of the current and future demands in terms of skills needed for every job. Current trends such as automation and robotization bring an added impact to anticipating talent development.
To tackle this challenge, we have developed:
(1) a comprehensive database of occupations and skills
(2) semantic analysis algorithms to recognize and classify job titles across industries
(3) job proximity algorithms to identify transition paths between jobs
In addition, our dataset incorporates variables measuring the degree of automation for the ensemble of skills and jobs. Automation indices are used to create scenarios on the amount of work performed by machines within a given organization. Knowing the volume and nature of skills predicted to be automated out, we estimate the amount of upskilling and reskilling needed for organizations in different industries.
This talk will raise awareness on the importance of skills (hard and soft) in career progression. The audience will learn how career paths can be built using a skill-based approach. We will also share quantitative results on the impact of automation on skills, jobs, and job families. Finally, we will present a methodology and results on how organizations can estimate the training needs to upskill and reskill their workforce within a 3-5 year horizon.
Bio: Gabrielle is the Head of Data Science at Boost.rs, a startup focusing on people professional development. In this role, Gabrielle is responsible for building and maintaining a world-class database of jobs and skills across 27 major industries. In addition, she develops algorithms to recommend meaningful career paths to the Boost.rs users and help them progress in their careers.
Prior to her startup experience, Gabrielle was a medical researcher in the field of brain imaging. She holds a PhD in physics from the Paris-Saclay University and an engineering degree from ESPCI ParisTech.
Gabrielle Fournet, PhD
Data Science Manager | Boostrs