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Key statistics

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

2 of 8

Track

Support

Family rungs priced

S1 · S2 · S3 · S4 · S5

19-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Provides growing technical support in field data collection and sample handling under general guidance. At the Support Specialist (S2) level, the role owns a defined queue or customer set, standard issues within known procedures, and drives customer satisfaction for own queue. None.

What this level does

Carries out multi-step field sampling routines across a survey site — running soil augers and soil core samplers, recording sample intervals and describing recovered material against a standard rock/soil classification key
Performs routine laboratory preparation and analysis of samples (crushing, splitting, sieving, mounting) for composition and structure testing following documented lab procedures
Digitizes field observations into GIS software and drafts preliminary geological maps and cross-sections from templates, flagging entries that don't fit the expected pattern
Compiles sample logs and QC checklists into preliminary data reports, checking for missing readings, mislabeled specimens or out-of-range values before submitting to a geologist

Knowledge applied: Broad knowledge of field and lab routines; carries out varied multi-step sampling and sample-prep tasks against general expectations, deadlines and priorities.
Complexity & problem solving: Semi-routine tasks; recognizes when a reading, sample or map entry deviates from the norm and flags it rather than resolving it alone.
Collaboration & interaction: Routine coordination with lab peers and field crew; delivers preliminary logs and drafts to geologists for review.
Typical experience: 1–2 years; some related field or laboratory experience.

Skills at this level

Sample Collection and Chain of Custody: — Collects rock, soil, water and mineral specimens in the field, labels and preserves them, and maintains chain-of-custody records so samples remain traceable and valid for laboratory analysis.
Field Data Logging: — Records site data — coordinates, sample intervals, lithology descriptions and environmental conditions — onto standard field sheets and into digital records for use by geologists.
Sampling Equipment Operation: — Sets up and operates soil augers, soil core samplers, hydraulic vibracorers and earth drills, selecting the right tool for ground conditions and troubleshooting recovery problems on site.
Laboratory Sample Analysis: — Prepares and analyzes rock, soil, water and mineral specimens — crushing, splitting, mounting and running composition and structure tests — following documented lab procedures.
Geological Mapping and Cross-Sections: — Produces geologic maps and cross-sections from field observations and survey data, drafting geological features to the accuracy needed for reports and regulatory submissions.
GIS and Geospatial Analysis: — Digitizes field and survey data into GIS software (e.g. ERDAS IMAGINE) and integrates remote-sensing and geospatial layers to build spatial datasets and geological base maps.
Geological Modeling Software: — Builds and edits geological models in packages such as Geosoft Oasis montaj and EarthVision, reconciling geophysical and geochemical datasets into coherent subsurface representations.
Geophysical and Remote Sensing Instruments: — Calibrates and operates ground-penetrating radar, remote sensing equipment and other survey instruments, and judges when re-runs or re-sampling are required for reliable data.
Data Quality Control: — Reviews sample logs, readings and map entries for missing, mislabeled or out-of-range values, reconciles discrepancies and corrects data before it reaches a geologist.
Environmental and Safety Compliance: — Monitors site conditions such as erosion and contamination, follows health and safety regulations during field and lab work, and documents deviations to support regulatory requirements.
Geological Data Records Management: — Enters and maintains sample and survey data in databases and spreadsheets (e.g. Microsoft Access), organizing records and templates so datasets stay consistent across projects.
Procedure Development for Sampling and Lab Work: — Defines and documents new sampling, sample-preparation and data-logging methods and QC standards, and establishes how new instruments are calibrated and used across the team.
Attention to Detail: — Maintains accuracy and precision in sample handling, measurement, data entry and map preparation so that downstream geological interpretation rests on reliable inputs.

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

Geology — 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

-22.9%Geoscientists, Except Hydrologists and Geographers · United States

29,200 → 22,510 jobs

2,000 openings / year, split into:

replacement / exits 1,919

Growth — new jobs (4%)Exits — backfill (96%)

4% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.2%
Growth share of hiring: 4%
Exit / retention pressure high: 96%
Openings / year: 2,000

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 S2 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$70k

San Francisco-Oakland-Fremont, CA$63k

Washington-Arlington-Alexandria, DC-VA-MD-WV$58k

Boulder, CO$57k

Seattle-Tacoma-Bellevue, WA$57k

Boston-Cambridge-Newton, MA-NH$55k

Lexington Park, MD$53k

Trenton-Princeton, NJ$53k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $42k; 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 S2 (S2 — Support Specialist) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A defined queue or customer set
Autonomy: General supervision; handles standard cases independently
Complexity: Standard issues within known procedures
Impact: Customer satisfaction for own queue
Decision rights: Resolves standard cases; escalates complex
Leadership: None

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

Promotion

The next rung from S2 is S3.

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
SVP of Geology	jf_geology::E2	$322,728†	confident0.06
Senior Geology Supervisor	jf_geology::M2	$110,455†	confident0.06
Geologist	jf_geology::P2	$72,357†	confident0.06
Geology Technician	jf_geology::S1	$37,323†	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 19-2042

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

S2

jf_geology::S2

Geology Field Technician

Geology

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: S
Superfunction: industrial_energy_operations
Function: geoscience
Family: geology
Universal level: 2 / 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").

Geomatics · S2review0.17

Geophysics · S2review0.17

Geothermal · S2review0.17

Petrophysics · S2review0.17

Technologist · S2review0.17

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 19-2042	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)