The Asia-Pacific mining industry experienced a 22% drop in new job postings in Q2 2023 compared with the previous quarter, with the highest share accounted for by Orica with 1,475 job postings, according to GlobalData’s analysis of mining company job postings. GlobalData’s Digging Deeper into Sustainability: Key Disruptive Forces in Mining report explores disruptive forces and innovation in the sector. It offers insights into the latest trends, deals, patents, and real-world innovations. Buy the report here.

Notably, Computer and Mathematical Occupations jobs accounted for a 12% share of the Asia-Pacific mining industry’s total new job postings in Q2 2023, drop 25% over the prior quarter.

Computer and Mathematical Occupations drive mining hiring activity

Computer and Mathematical Occupations, with a share of 12% new job postings, was the occupation with the greatest hiring activity in the Asia-Pacific mining industry in Q2 2023 , ahead of Architecture and Engineering Occupations with a 10% share of new job postings.

The other prominent roles included Management Occupations with a 9% share in Q2 2023, Business and Financial Operations Occupations with an 8% share and Office and Administrative Support Occupations with a 6% share of new job postings.

Top five companies accounted for 43% of hiring activity

Orica posted 1,475 jobs in Q2 2023 and registered a decline of 26% over the previous quarter, followed by Cummins with 1,432 jobs and a 69% growth. ABB, with 769 jobs, and Caterpillar, with 729 jobs, recorded a 20% drop and a 12% drop, respectively, while Glencore recorded a 117% increase with a 728 new job postings during Q2 2023.

Regional analysis of hiring in the Asia-Pacific mining industry, Q2 2023

Australia held the leading share of the Asia-Pacific mining hiring activity with a 41.16% share, a 31% decrease over Q1 2023. India was next with 31.98%, four-percentage-point down over the previous quarter.

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This content was updated on 24 July 2023


GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Jobs Analytics uses machine learning to uncover key insights from tracking daily job postings for thousands of companies globally. Proprietary analysis is used to group jobs into key thematic areas and granular sectors across the world’s largest industries. classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.