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Key statistics

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

3 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

19-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Executive responsible for setting enterprise-wide agronomic strategy, soil and crop management standards, and land-use policy across all company operations. At the Vice President (E3) level, the role owns a division, market and competitive strategy, and drives division-wide. Leads a division's leadership team.

What this level does

Leads a major agronomic business area — a large division or multi-region agronomy portfolio — through senior executives, bearing enterprise-level risk on crop-program performance
Shapes corporate agronomic strategy: which crop systems, geographies and precision-ag/remote-sensing capabilities the company invests in over multi-year horizons
Represents the company's agronomic science externally to regulators, industry bodies, and major grower and channel partners as a recognized authority
Owns the enterprise R&D-to-commercialization pipeline for agronomic innovation (variable-rate, NDVI/remote-sensing analytics, agronomic modeling)
Sets division-level policy on stewardship, resource-use efficiency and sustainable-practice commitments that carry reputational and regulatory consequence

Knowledge applied: Shapes corporate agronomic strategy for large divisions or multi-region portfolios; sets long-horizon investment direction across crop systems, geographies and precision-ag capabilities.
Complexity & problem solving: Manages enterprise-level agronomic risk with critical strategic impact — pipeline, stewardship and resource-efficiency decisions carrying reputational and regulatory weight.
Collaboration & interaction: Represents the company externally to regulators, industry bodies and major partners, participating in strategy at the enterprise level; leads major business areas through senior executives.
Typical experience: 15–20+ years with demonstrated enterprise-impact agronomic leadership.

Skills at this level

Strategic planning: — Sets agronomic strategy and trial/investment priorities across regions and product lines, aligning crop-science direction with organizational and market goals.
Agronomic modeling: — Directs advanced modeling of crop and soil systems to forecast yield and resource-use outcomes that inform portfolio and product-line investment decisions.
Precision agriculture: — Governs enterprise deployment of geospatial and variable-rate technologies — yield mapping, variable-rate seeding and irrigation — as a strategic capability across the business.
Remote-sensing analytics: — Sets strategy for satellite/drone NDVI imagery programs that compare topography with soil, fertility, pest and weather data to guide large-scale agronomic decisions.
Regulatory compliance: — Establishes the agronomic regulatory and stewardship posture across business units, ensuring pesticide, fertility and field-practice programs meet agricultural regulations.
Stakeholder negotiation: — Negotiates critical agronomic licensing, supply and partnership matters with trait providers, ag-tech vendors and major grower cooperatives at the executive level.
Program management: — Oversees enterprise agronomic programs and trial networks, allocating agronomist and technician resources and securing grant and research funding.
Nutrient and fertility management: — Sets enterprise standards for analyzing nutrient levels and building fertilizer recommendations from soil, plant and water data across the crop portfolio.
Integrated Pest Management (IPM): — Directs the strategy for identifying and controlling pests, diseases and agronomic risks using IPM approaches at the division and enterprise scale.
Irrigation and water management: — Governs enterprise policy on soil and water management, crop rotation and irrigation practice as part of resource-use-efficiency commitments.
Data analysis: — Translates multi-year, large-scale crop-yield and soil datasets into commercial recommendations and enterprise strategic direction.
Experimental design: — Approves trial and experimental methodologies across the agronomy function to ensure new crop varieties, fertility and pest-control tests yield decision-grade evidence.
Soil science / soil chemistry: — Applies expert understanding of soil chemical, physical, biological and mineralogical composition to set the scientific basis for enterprise crop-production strategy.
Plant biology / plant physiology: — Grounds portfolio and R&D decisions in deep knowledge of plant biology and physiology underpinning crop growth, breeding and production.

Model-authored from 7 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

Agronomist — 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

+17.3%Soil and Plant Scientists · United States

14,150 → 16,600 jobs

1,700 openings / year, split into:

replacement / exits 1,588

Growth — new jobs (7%)Exits — backfill (93%)

7% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +5.4%
Growth share of hiring: 7%
Exit / retention pressure high: 93%
Openings / year: 1,700

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 E3 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$587k

San Francisco-Oakland-Fremont, CA$526k

Washington-Arlington-Alexandria, DC-VA-MD-WV$487k

Boulder, CO$480k

Seattle-Tacoma-Bellevue, WA$480k

Boston-Cambridge-Newton, MA-NH$460k

Lexington Park, MD$448k

Trenton-Princeton, NJ$445k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $352k; 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 E3 (E3 — Vice President) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A division
Autonomy: Accountable for division strategy and P&L
Complexity: Market and competitive strategy
Impact: Division-wide
Decision rights: Owns division strategy, budget, and org
Leadership: Leads a division's leadership team

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

Promotion

The next rung from E3 is E4.

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
Agronomy Manager	jf_agronomist::M3	$120,351†	confident0.06
Agronomist	jf_agronomist::P3	$82,468†	confident0.06
Senior Agronomy Technician	jf_agronomist::S3	$49,566†	confident0.06
SVP of Agronomy	jf_agronomist::E2	$322,728†	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 19-1013

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

E3

jf_agronomist::E3

Chief Agronomy Officer

Agronomist

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: E
Superfunction: industrial_energy_operations
Function: engineering_expansion
Family: agronomist
Universal level: 3 / 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").

Aeronautical · E3review0.17

Agricultural · E3review0.17

Application Services · E3review0.17

Chemical · E3review0.17

Communication · E3review0.17

Electrical Engineering · E3review0.17

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 19-1013	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)