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December 17, 2021updated 01 Feb 2022 11:47am

Where is food industry’s hiring for machine-learning jobs buoyant?

By Michael Goodier

Europe was the fastest-growing region in the field of hiring for machine-learning roles among food manufacturers in the three months ending October, GlobalData analysis shows.

The number of positions in Europe made up 17.3% of the total machine-learning jobs monitored by GlobalData in the food industry – up from 9% in the same quarter last year.

That was followed by Asia-Pacific, which saw a 6.1 year-on-year percentage point rise in its share of machine-learning roles.

The figures are compiled by GlobalData, which tracks the number of new job postings from key companies in various sectors over time. Using textual analysis, these job advertisements are then classified thematically.

GlobalData’s thematic approach to sector activity seeks to group key company information by topic to see which companies are best placed to weather the disruptions coming to their industries.

By tracking job ads, it allows GlobalData to see which companies are leading the way on specific issues and which are dragging their heels – and importantly where the market is expanding and contracting.

Which countries are seeing the most growth for machine learning roles in the food industry?

The fastest-growing country was the United Kingdom, which saw 1.4% of all machine-learning job adverts in the three months ending October 2020, increasing to 8.2% in the three months ending October this year.

That was followed by Spain (up 3.2 percentage points), India (up 3.1), and Singapore (up 1.8).

Nevertheless, the top country for machine-learning roles in the food industry was the United States, which accounted for 35.5% of all roles in the three months ending October.

Robots and automation in the logistics chain and the factory – and perhaps even more in customer service and clerical offices – may indeed offer productivity and resilience that could mean success but they don’t always scale fast when needed. Meanwhile, machine-learning AI is a mantra for investors and analysts but is sometimes difficult to turn into a genuine advantage.

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