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Key statistics

The identity block — every fact is canon, none is generated.

6 of 8

Track

Management

Family rungs priced

M1 · M2 · M3 · M4 · M5 · M6

11-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Senior executive leading all ore crushing, grinding, and metal extraction and refining operations across one or more processing plants. At the Vice President (M6) level, the role owns a major function or division, enterprise priorities and external factors, and drives division-wide / organization-wide. Leads the leadership of a division.

What this level does

Lead processing operations across multiple plants, functions or a division, shaping long-term strategy that affects overall company success.
Set the direction for how the orebody feeds the process across sites — driving geometallurgy, resource modelling and equipment-selection strategy for current and future operations.
Direct through senior managers, resolving abstract cross-functional issues spanning geology, metallurgy, maintenance, environmental and commercial functions.
Negotiate with executives, regulators and major partners on critical production, capital and compliance matters, acting as a policy influencer for processing standards.
Sponsor multi-year, business-wide continuous-improvement and capital programs that reposition processing capability and cost structure.

Knowledge applied: Sets long-term processing strategy across multiple plants or a division, spanning resource evaluation through recovery.
Complexity & problem solving: Addresses abstract, cross-functional issues spanning geology, metallurgy, environment and commercial factors.
Collaboration & interaction: Negotiates with executives and regulators on critical matters; influences processing policy across the business.
Typical experience: 12–15+ years of deep leadership across processing departments or divisions.

Skills at this level

Safety and Environmental Compliance: — Ensures mineral processing operations meet environmental regulations and safety standards, maintaining risk assessments, defect reporting and regulatory standing across plant circuits.
Process Plant Operation: — Operates and monitors all areas of the processing plant — crushing, screening, milling, thickening, leaching, CIL and gold/metal recovery — observing meters, gauges and control panels to keep circuits running safely and efficiently.
Process Optimization: — Makes changes in plant processes to optimize throughput, recovery and efficiency, tuning operating parameters against production targets and cost.
Machine Setup and Operation: — Sets up and operates stationary plant and machinery that grind, crush, cut, saw and slice rocks, minerals and stones according to job specifications.
Malfunction Detection and Maintenance Support: — Detects equipment malfunctions from meter and control-panel readings and supports plant and machinery maintenance and repair, reporting plant defects for resolution.
Shift Production Recording: — Records information about processing completed during shifts, including quantities, types and dimensions of materials produced, for handover and reporting.
Team Leadership and Mentoring: — Manages a mineral processing team, defining roles and responsibilities, mentoring and motivating operators and metallurgists, and driving continuous improvement.
Technical Problem Solving: — Solves complex material and process-related problems in the plant, providing technical expertise and coaching to metallurgists, technicians and refiners.
Plant Budget and Cost Management: — Owns operating budgets and consumables (grinding media, reagents) for the plant, managing cost per tonne and prioritizing improvement and capital-related spend.
Geometallurgy and Resource Integration: — Integrates orebody and feed characteristics into plant operation and equipment selection through familiarity with geometallurgy and resource modelling.
Regulated Qualifications: — Achieves and maintains appropriate regulated operating qualifications, such as the MPQC Level 2 Diploma in Mineral Products Mobile Plant Operations, and supports team certification.
Continuous Improvement Program Leadership: — Undertakes and sponsors projects and multi-year programs to improve production plant performance, managing consultants and cross-functional stakeholders.

Model-authored from 18 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Mining Processing Plant — median with , by . Real canon data.

National-base pricing — this family's function differential is pending review, so dollar levels are not function-adjusted (level-over-level % is unaffected).

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 11-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+26.2%Industrial Production Managers · United States

185,790 → 234,380 jobs

17,100 openings / year, split into:

replacement / exits 16,640

Growth — new jobs (3%)Exits — backfill (97%)

3% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +1.9%
Growth share of hiring: 3%
Exit / retention pressure high: 97%
Openings / year: 17,100

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level M6 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$415k

San Francisco-Oakland-Fremont, CA$373k

Washington-Arlington-Alexandria, DC-VA-MD-WV$345k

Boulder, CO$340k

Seattle-Tacoma-Bellevue, WA$340k

Boston-Cambridge-Newton, MA-NH$325k

Lexington Park, MD$317k

Trenton-Princeton, NJ$315k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $249k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates M6 (M6 — Vice President) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A major function or division
Autonomy: Accountable for division strategy and outcomes
Complexity: Enterprise priorities and external factors
Impact: Division-wide / organization-wide
Decision rights: Owns strategy, budget, and org for a division
Leadership: Leads the leadership of a division

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

M6is the top of this family's ladder — progression from here is a lattice move (see adjacent roles below), not a rung.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
Principal Process Metallurgist	jf_mining_processing_plant::P6	$188,314†	confident0.06
Director, Mineral Processing Plant	jf_mining_processing_plant::M5	$188,371†	confident0.06
Staff Mineral Processing Engineer	jf_mining_processing_plant::P5	$138,423†	confident0.12
Lead Mineral Processing Specialist	jf_mining_processing_plant::S5	$60,631†	confident0.12

†National-base pricing — this family's function differential is pending review, so the dollar level is not function-adjusted.

Capability cluster

O*NET 11-3051

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

M6

jf_mining_processing_plant::M6

Senior Director of Mining Processing Plant Operations

Mining Processing Plant

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: M
Superfunction: industrial_energy_operations
Function: plant_operations
Family: mining_processing_plant
Universal level: 6 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Nuclear Power Plant · M6review0.17

Plant Maintenance (Energy/Mining) · M6review0.17

Plant Operations (Energy/Mining) · M6review0.17

Power Plant Management · M6review0.17

Refinery · M6review0.17

Renewables Plant · M6review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 11-3051	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)