Lead Mine Planning & Probabilistic Scheduling (Australia)

BHP Group; Australia; On-site; AUD 180,000 - 240,000; Full time

Benefits offered by this job

Performance bonuses

Employee share plan

Flexible working options

Generous parental leave

Parent rooms

Job summary

BHP Group is seeking a Principal Mine Planning professional to drive the Enterprise Mining Probabilistics (EMP) deployment across multiple sites in Australia. You will partner with leadership, mine planning and operations teams to implement phased deployment for FY27 and beyond, with expected site travel.

The role requires strong background in mining engineering, planning software, and experience in supervision, enabling robust probabilistic planning and continuous improvement within our mining

Qualifications

• Experience with mine planning and scheduling software.
• Background in mine planning and scheduling; operational supervision is a plus.
• Strong engineering background across mining-related disciplines.

Responsibilities

• Drive EMP Deployment activities across a phased deployment strategy.
• Engage with Australian customers across leadership, mine planning and operations to define/drive EMP Deployment for FY27; site travel required.
• Apply probabilistic methods, variability management and systems thinking in mine planning and operations.
• Participate in EMP team routines using Agile Project Management Framework (APMF).
• Provide internal support for EMP artefacts, resources and tools.

Skills

Mine planning

Scheduling

Team collaboration

Stakeholder engagement

Education

Mining Engineering degree

Job description

BHP Group is seeking a Principal Mine Planning professional to drive the Enterprise Mining Probabilistics (EMP) deployment across multiple sites in Australia. You will partner with leadership, mine planning and operations teams to implement phased deployment for FY27 and beyond, with expected site travel.

The role requires strong background in mining engineering, planning software, and experience in supervision, enabling robust probabilistic planning and continuous improvement within our mining