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Key statistics

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

5 of 8

Track

Individual contributor

Family rungs priced

P1 · P2 · P3 · P4 · P5 · P6

19-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Serves as the organization's top technical authority on emissions monitoring, measurement methods, and compliance strategy across energy and mining operations. At the Expert Professional (P5) level, the role owns multiple systems or a technical domain, establishes the approach, and drives org / multi-team outcomes. Leads cross-team technical initiatives.

What this level does

Shape and drive the organization's strategic approach to emissions reduction, integrating clean energy procurement, decarbonization pathways, and sustainability targets into multi-year roadmaps
Act independently on broad, ambiguous assignments where reduction strategy, market participation, and cost outcomes are intangibles rather than defined calculations
Represent the company as a technical spokesperson to regulators, auditors, and external partners on emissions methodology, targets, and program credibility
Design significantly improved emissions accounting and forecasting methods that go beyond standard factors, building the mental models the wider team adopts
Influence enterprise-wide commercial and operational decisions by connecting emissions performance to portfolio strategy across RA, Energy, GHG, and LCFS markets

Knowledge applied: Brings strategic, expert-level command of decarbonization, clean-energy procurement, and emissions markets to broad and unique assignments, designing improved methods beyond standard practice.
Complexity & problem solving: Works with intangibles and high independence on strategic issues that contribute to company objectives; refines its own mental models against feedback.
Collaboration & interaction: Builds influential internal and external networks; acts as spokesperson to regulators and partners.
Typical experience: 12+ years with extensive emissions and energy-strategy expertise.

Skills at this level

Emissions calculations and modeling: — Performs quantitative emissions analyses including energy and carbon emissions calculations, thermal comfort analysis, LCCA, LCA, and whole-building energy and performance models to quantify facility and portfolio impact.
CEMS data management: — Configures, operates, and validates Continuous Emissions Monitoring Systems to produce defensible real-time emissions data streams for regulatory reporting.
PLC / data acquisition programming: — Uses and programs PLCs, data loggers, and data acquisition software to capture and route continuous emissions monitoring signals into reporting systems.
Multi-media environmental compliance: — Manages compliance obligations across air quality permitting, stormwater/NPDES/industrial discharge, and hazardous materials/waste programs, reconciling emissions inventories against permitted limits.
Sustainability metric tracking: — Measures, tracks, and validates Scope 1, 2, and 3 emissions along with energy, water, and waste metrics against company reduction goals.
Emissions data extraction and analysis: — Extracts, cleans, and analyzes emissions and environmental data with a focus on accuracy in collection, validation, and technical reporting.
Emissions reporting and dashboards: — Builds recurring emissions and sustainability reports and dashboards in Tableau, Power BI, or similar tools to make CEMS and inventory data actionable for stakeholders.
Regulatory emissions reporting: — Prepares and reviews periodic mandated submissions such as annual criteria and toxics emissions reports, ensuring methodology is defensible to regulators and auditors.
Environmental credit and allowance markets: — Tracks and performs portfolio analysis on environmental credits and allowances (RA, Energy, CRR, GHG, LCFS) to support the organization's commercial and compliance positions.
Environmental Management System (EMS) administration: — Implements and maintains the company's EMS, reviewing and revising HSE guidelines and procedures governing emissions and multi-media compliance.
Excel-based emissions analysis: — Uses advanced Excel and Office 365 capabilities to structure, calculate, and audit emissions datasets and factor-based inventories.
Decarbonization and clean-energy procurement strategy: — Shapes and drives the organization's approach to clean energy procurement, emissions reduction pathways, and enterprise decarbonization roadmaps.

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

Emissions — 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 19-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+0.8%Environmental Scientists and Specialists, Including Health · United States

84,290 → 84,930 jobs

8,500 openings / year, split into:

replacement / exits 8,103

Growth — new jobs (5%)Exits — backfill (95%)

5% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +4.4%
Growth share of hiring: 5%
Exit / retention pressure high: 95%
Openings / year: 8,500

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 P5 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$225k

San Francisco-Oakland-Fremont, CA$202k

Washington-Arlington-Alexandria, DC-VA-MD-WV$187k

Boulder, CO$184k

Seattle-Tacoma-Bellevue, WA$184k

Boston-Cambridge-Newton, MA-NH$176k

Lexington Park, MD$172k

Trenton-Princeton, NJ$171k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $135k; 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 P5 (P5 — Expert Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple systems or a technical domain
Autonomy: Sets direction within the domain
Complexity: Novel, high-ambiguity problems; establishes the approach
Impact: Org / multi-team outcomes
Decision rights: Authority over a technical domain
Leadership: Leads cross-team technical initiatives

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

Promotion

The next rung from P5 is P6.

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
Chief Emissions Officer	jf_emissions::E5	$340,737†	confident0.06
Director of Emissions	jf_emissions::M5	$188,371†	confident0.06
Lead Emissions Specialist	jf_emissions::S5	$60,631†	confident0.06
Senior Emissions Analyst	jf_emissions::P4	$109,466†	confident0.06

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

Capability cluster

O*NET 19-2041

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

P5

jf_emissions::P5

Staff Emissions Engineer

Emissions

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: P
Superfunction: industrial_energy_operations
Function: energy_utilities_business_operations
Family: emissions
Universal level: 5 / 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").

Assets · P5review0.17

Control Operations · P5review0.17

Energy Grid · P5review0.17

Energy Operations · P5review0.17

Land / Property · P5review0.17

Mining Operations · P5review0.17

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 19-2041	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)