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Key statistics

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

1 of 8

Track

Support

Family rungs priced

S1 · S2 · S3 · S4 · S5

35-0000

retail_hospitality

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Entry-level team member who greets guests, takes and delivers orders, prepares simple drinks, and clears tables in a restaurant. At the Support Associate (S1) level, the role owns a single task type or queue, routine, well-defined requests, and drives individual transactions. None.

What this level does

Greet diners at the host stand and seat guests to assigned tables following the posted seating chart and reservation notes
Take food and beverage orders at an assigned station and enter them into the POS (Toast, PixelPoint or NCR) exactly as trained
Run plated food from the pass to the correct table and clear/reset tables as a busser between seatings
Deliver ordered items to the table and check back on guests using the standard service-step sequence
Ask a supervisor when a guest request, substitution or table situation falls outside the trained routine

Knowledge applied: General knowledge of the service-step routine and basic POS order entry; performs prescribed host, server, busser and runner tasks with answers readily available from a supervisor or trainer.
Complexity & problem solving: Routine, prescribed tasks — seat guests, take and run orders, reset tables; anything outside the script is referred up.
Collaboration & interaction: Standard guest interactions and station-level handoffs; completes own assigned tasks under close supervision.
Typical experience: 0–1 years; minimal restaurant floor experience.

Skills at this level

Multitasking: — Handles multiple guest-facing service tasks at once — greeting, order-taking, running, check-outs — while working under the pressure of a full section or rush.
Interpersonal Skills: — Maintains a friendly demeanor and stays attentive to guests' needs throughout the meal, reading table cues to time service touches in dining service delivery.
Active Listening: — Gives full attention to guest orders, special requests and complaints, confirming the points being made to ensure orders and resolutions are accurate at the table.
Coordination: — Adjusts service actions in relation to the kitchen pass and fellow servers to run the floor-to-kitchen interface so courses fire and land in the right sequence and timing.
Speaking: — Communicates specials, menu descriptions, wait times and service instructions clearly to guests and to floor staff during service.
Monitoring: — Assesses one's own service performance and the state of stations, supplies and work areas against service standards to take corrective action before it reaches the guest.
Point of Sale (POS) Transaction Handling: — Enters orders, presents bills, processes payments and splits, and applies comps, voids, discounts and refunds within authority on restaurant POS systems (Toast, PixelPoint, NCR NeighborhoodPOS).
Tableside Service Techniques: — Performs elevated table service such as carving meat, preparing flambe dishes, and serving wine and liquor to the guest at the table.
Guest Complaint Resolution: — Resolves customer complaints regarding food and service at the table — wait times, order errors, dining-experience issues — recovering the guest and documenting the outcome.
Shift Floor Coordination: — Assigns duties, responsibilities and work stations to floor staff in line with cover volume and re-balances sections to keep the floor running smoothly across a shift.
Cash and Transaction Reconciliation: — Reconciles a shift's cash drawer and POS transactions, investigating discrepancies in comps, refunds and payments to keep the shift's takings accurate.
Service Standards Development: — Contributes to creating and standardizing seating flows, service-step scripts, opening/closing checklists and comp/void policies for a station, shift or venue.

Model-authored from 16 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

Front of House — 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 35-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+0.9%Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop · United States

423,380 → 427,150 jobs

107,700 openings / year, split into:

replacement / exits 108,345

Growth — new jobs (-1%)Exits — backfill (100%)

This occupation is projected to contract — every opening is replacing someone leaving, not net new demand.

Projected growth 2024–34 contracting: -1.5%
Growth share of hiring: -1%
Exit / retention pressure high: 100%
Openings / year: 107,700

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 S1 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$61k

San Francisco-Oakland-Fremont, CA$54k

Washington-Arlington-Alexandria, DC-VA-MD-WV$50k

Boulder, CO$50k

Seattle-Tacoma-Bellevue, WA$50k

Boston-Cambridge-Newton, MA-NH$48k

Lexington Park, MD$46k

Trenton-Princeton, NJ$46k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $36k; 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 S1 (S1 — Support Associate) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A single task type or queue
Autonomy: Close supervision; follows defined procedures
Complexity: Routine, well-defined requests
Impact: Individual transactions
Decision rights: Acts within scripts; escalates exceptions
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 S1 is S2.

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
Front of House Supervisor	jf_front_of_house::M1	$85,619†	confident0.06
Front of House Associate	jf_front_of_house::P1	$61,862†	confident0.06
Server	jf_front_of_house::S2	$42,923†	confident0.06
Front of House Senior Supervisor	jf_front_of_house::M2	$110,455†	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 35-9031

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

S1

jf_front_of_house::S1

Front of House Associate

Front of House

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: retail_hospitality
Function: restaurant_dining_operations
Family: front_of_house
Universal level: 1 / 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").

Back of House · S1review0.17

Catering · S1review0.17

Chef · S1review0.17

Restaurant Management · S1review0.17

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 35-9031	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)