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Key statistics

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

1 of 8

Track

Management

Family rungs priced

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11-0000

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Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

First-line manager overseeing a small team of downstream process development scientists and associates. At the Manager (Team Lead) (M1) level, the role owns a single team, day-to-day delivery and people issues, and drives team output and health. Direct people management of one team.

What this level does

Supervises a unit of scientists executing lab-scale chromatography, filtration, and UFDF experiments, assigning daily bench work and reviewing experimental data for accuracy
Ensures accurate and timely documentation in electronic laboratory notebooks and technical reports across the team
Coordinates with upstream/downstream process development and process analytical groups on sample hand-offs and experimental schedules
Trains junior scientists on established purification methods, HPLC/UPLC characterization, and lab safety practices
Manages equipment operations for chromatography systems and filtration technologies within the unit

Knowledge applied: Functional expert in downstream unit operations (chromatography, filtration, UFDF) with some leadership exposure; applies established purification practices to a defined unit's work.
Complexity & problem solving: Limited scope; resolves routine experimental and documentation issues using established methods and protocols.
Collaboration & interaction: Daily interactions with bench staff and peer groups in upstream, downstream, and process analytical development.
Typical experience: Functional expertise in downstream purification with initial supervisory responsibility over individual contributors.

Skills at this level

Chromatography: — Directs purification strategy using multiple chromatographic modes (SEC, RP, IEX, HILIC, affinity) to separate biological products and remove product- and process-related impurities.
Filtration: — Oversees downstream filtration unit operations — depth filtration, viral filtration, membrane filtration, and TFF — for clarification and concentration of biologic products.
Ultrafiltration/Diafiltration (UFDF/TFF): — Guides membrane-based concentration and buffer-exchange operations to reach target formulation conditions for biologic products.
Scale-down model development: — Leads building and qualifying robust scale-down models used for process characterization and continued process improvement of commercial products.
Statistical process design: — Applies and champions statistical design and analysis of experiments to establish robust, well-characterized manufacturing process parameters.
Technology transfer: — Manages transfer of downstream processes from lab to GMP manufacturing, coordinating scale-up, batch records, and cross-functional stakeholder alignment.
Protein characterization: — Oversees analysis of purified proteins to assess purity, yield, and clearance of product variants and process-related impurities across development stages.
Analytical method development/validation: — Directs design, execution, and validation of characterization and release/stability methods per ICH Q2 (R2) guidance to support process decisions.
Spectroscopy (PAT): — Guides deployment of Raman, FTIR, and NIR spectroscopy as Process Analytical Technology to measure and control downstream operations in real time.
Chemometrics / multivariate modeling: — Applies multivariate modeling and data-analysis approaches to interpret combined process and analytical data and inform control strategy.
Data science / digital modeling: — Leverages data science and advanced modeling to build digital platforms for biophysical, process, economic, and multivariate visualization and analysis.
CMC regulatory authoring: — Directs authoring and review of CMC sections of regulatory submissions (IND, BLA), ensuring downstream process data supports filing strategy.
Process troubleshooting and investigations: — Leads root-cause investigation and resolution of downstream process deviations during scale-up, validation, and commercial manufacturing support.
Team leadership and technical mentoring: — Builds and develops downstream scientists and engineers, coaching on purification science and driving alignment on technical strategy across matrixed teams.
External partnership and thought leadership: — Represents the organization as a downstream bioprocess expert through conferences, publications, patents, and collaborations with academia, industry, and vendors.

Model-authored from 14 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

No priced rungs for this family's ladder yet.

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

+8.3%Architectural and Engineering Managers · United States

194,250 → 210,340 jobs

14,500 openings / year, split into:

replacement / exits 13,693

Growth — new jobs (6%)Exits — backfill (94%)

6% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.8%
Growth share of hiring: 6%
Exit / retention pressure high: 94%
Openings / year: 14,500

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 M1 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$143k

San Francisco-Oakland-Fremont, CA$128k

Washington-Arlington-Alexandria, DC-VA-MD-WV$118k

Boulder, CO$117k

Seattle-Tacoma-Bellevue, WA$117k

Boston-Cambridge-Newton, MA-NH$112k

Lexington Park, MD$109k

Trenton-Princeton, NJ$108k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $86k; 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 M1 (M1 — Manager (Team Lead)) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A single team
Autonomy: Manages within established goals
Complexity: Day-to-day delivery and people issues
Impact: Team output and health
Decision rights: Owns team execution, hiring input, performance
Leadership: Direct people management of one 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 M1 is M2.

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
Cost Accounting Supervisor	jfo_jfm_accounting-cost-accounting::M1	—	confident0.00
General Accounting Supervisor	jfo_jfm_accounting-general-accounting::M1	—	confident0.00
Administrative Support Supervisor	jfo_jfm_administrative-corporate-services-administrative-support::M1	—	confident0.00
Service Delivery Supervisor	jfo_jfm_administrative-corporate-services-service-delivery::M1	—	confident0.00

Capability cluster

O*NET 11-9041

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

M1

jfo_jfm_process-analytical-development-downstream-process-developmen::M1

Downstream Process Development Supervisor

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
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").

jfo_jfm_accounting-cost-accounting::M1 · M1confident0.00

jfo_jfm_accounting-general-accounting::M1 · M1confident0.00

jfo_jfm_administrative-corporate-services-administrative-support::M1 · M1confident0.00

jfo_jfm_administrative-corporate-services-service-delivery::M1 · M1confident0.00

jfo_jfm_aerospace-propulsion-engineering-aerospace-engineering::M1 · M1confident0.00

jfo_jfm_aerospace-propulsion-engineering-propulsion-engineering::M1 · M1confident0.00

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 11-9041	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)