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Job description template

Growth Marketer Job Description Template (2026)

A free, copy-ready Growth Marketer job description covering responsibilities, must-have skills, tools, seniority variants, and KPIs. Written for hiring managers, not for SEO filler.

Hire a pre-vetted growth marketer

Key facts

Role
Growth Marketer
Reports to
Reports to the Head of Growth
Must-have skills
7 items
Seniority tiers
Junior / Mid / Senior
KPIs defined
6 metrics
Starting price (offshore)
$2400/month

Role summary

A Growth Marketer runs structured experimentation across the AARRR funnel: acquisition, activation, retention, referral, revenue. Partners with product and engineering on in-product tests behind feature flags, instruments events in Mixpanel/Amplitude/PostHog, prioritizes experiments via ICE/PIE, runs proper A/B tests with power analysis, and is accountable for moving activation rate, retention cohorts, and CAC payback — not for executing any one channel.

Responsibilities

Must-have skills

  • • 4+ years in growth, product marketing, or PLG-focused marketing with direct experiment ownership.
  • • SQL fluency: can write joins and window functions to slice cohorts and funnels without waiting on data.
  • • Experimentation platform hands-on (Statsig, GrowthBook, Optimizely, LaunchDarkly, or Eppo) including power analysis and sequential testing awareness.
  • • Product analytics: Mixpanel, Amplitude, Heap, or PostHog at a fluent level — can build funnels, cohorts, and retention reports, audit event schemas.
  • • Funnel frameworks: AARRR, HEART, or jobs-to-be-done; understands activation metrics specific to the product.
  • • Statistics literacy: p-values, MDE, sample ratio mismatch, novelty effects, peeking — and knows why each matters.
  • • Lifecycle platform: built flows in Customer.io, Klaviyo, Braze, or Iterable beyond drag-and-drop templates.

Nice-to-have skills

  • • Product-led growth experience (freemium, self-serve, PQL scoring).
  • • Referral loop design: has shipped a Dropbox/Notion/Typeform-style referral program.
  • • Python or R for custom analysis (survival curves, uplift modeling).
  • • Bayesian experiment platform experience (Statsig, Eppo) in addition to frequentist.
  • • Cross-functional experience in onboarding, pricing, or packaging experiments.
  • • Experience with a CDP (Segment, RudderStack) for event instrumentation.

Tools and technology

Reporting structure

Reports to the Head of Growth, VP Marketing, or directly to a PLG-focused founder. Works daily with Product Managers (in-product experiments), Engineering (feature flags, instrumentation), Data (metric definitions, warehouse), and Lifecycle/Paid marketing on cross-funnel tests.

Seniority variants

How responsibilities shift across junior, mid, and senior levels.

junior

2-3 years

  • • Execute experiments designed by a senior: build the variant, QA the tracking, report results.
  • • Pull cohort and funnel reports; flag anomalies.
  • • Build lifecycle flows under review; maintain event taxonomy.
  • • Write up experiment post-mortems.

mid

4-6 years

  • • Own a funnel stage (activation OR retention OR acquisition) with experiment velocity accountability.
  • • Design and ship experiments independently with proper power analysis.
  • • Pair with engineering on in-product tests without hand-holding.
  • • Hit activation/retention improvement targets quarterly.

senior

7+ years

  • • Set the full growth strategy and experiment roadmap.
  • • Build the growth model: CAC, LTV, payback, viral coefficient; own the assumptions.
  • • Lead a team of growth marketers and/or own cross-functional initiatives.
  • • Present to leadership on growth levers, unit economics, and PLG motion health.

Success metrics (KPIs)

Full JD (copy-ready)

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# Growth Marketer — Job Description

## Role summary
A Growth Marketer runs structured experimentation across the AARRR funnel: acquisition, activation, retention, referral, revenue. Partners with product and engineering on in-product tests behind feature flags, instruments events in Mixpanel/Amplitude/PostHog, prioritizes experiments via ICE/PIE, runs proper A/B tests with power analysis, and is accountable for moving activation rate, retention cohorts, and CAC payback — not for executing any one channel.

## Responsibilities
- Own the experiment roadmap across the full funnel (AARRR) and maintain a weekly experiment log with hypothesis, metric, result, and decision.
- Instrument event tracking in Mixpanel, Amplitude, Heap, or PostHog with a clean taxonomy; audit and fix tracking debt before new tests.
- Run A/B tests through Statsig, GrowthBook, Optimizely, or LaunchDarkly with proper randomization, exposure, sample sizing, and significance.
- Prioritize experiments via ICE or PIE scoring — reject pet projects that cannot clear the threshold.
- Pair with product managers and engineers on in-product onboarding, empty states, tooltips, and aha-moment redesign.
- Build lifecycle flows in Customer.io, Klaviyo, or Braze for activation, feature adoption, reactivation, and expansion.
- Run cohort retention analysis (weekly retention curves, Day-N retention) to validate whether changes moved long-term behavior, not just short-term vanity metrics.
- Model CAC, LTV, payback, and viral coefficient; push back on spend that cannot earn payback inside the business target.
- Ship acquisition experiments: landing page tests, channel exploration, referral loops, SEO content tests.
- Own the growth dashboard: funnel conversion by stage, cohort retention, experiment velocity, experiment win rate.
- Run a weekly growth review with product, engineering, and marketing to align on what ships next and what gets killed.
- Write pre-mortems and post-mortems on every material experiment; document learnings so the team does not rediscover the same thing.

## Must-have skills
- 4+ years in growth, product marketing, or PLG-focused marketing with direct experiment ownership.
- SQL fluency: can write joins and window functions to slice cohorts and funnels without waiting on data.
- Experimentation platform hands-on (Statsig, GrowthBook, Optimizely, LaunchDarkly, or Eppo) including power analysis and sequential testing awareness.
- Product analytics: Mixpanel, Amplitude, Heap, or PostHog at a fluent level — can build funnels, cohorts, and retention reports, audit event schemas.
- Funnel frameworks: AARRR, HEART, or jobs-to-be-done; understands activation metrics specific to the product.
- Statistics literacy: p-values, MDE, sample ratio mismatch, novelty effects, peeking — and knows why each matters.
- Lifecycle platform: built flows in Customer.io, Klaviyo, Braze, or Iterable beyond drag-and-drop templates.

## Nice-to-have skills
- Product-led growth experience (freemium, self-serve, PQL scoring).
- Referral loop design: has shipped a Dropbox/Notion/Typeform-style referral program.
- Python or R for custom analysis (survival curves, uplift modeling).
- Bayesian experiment platform experience (Statsig, Eppo) in addition to frequentist.
- Cross-functional experience in onboarding, pricing, or packaging experiments.
- Experience with a CDP (Segment, RudderStack) for event instrumentation.

## Tools and technology
- Mixpanel / Amplitude / PostHog / Heap
- Statsig / GrowthBook / Optimizely / LaunchDarkly
- Customer.io / Klaviyo / Braze
- Segment / RudderStack
- GA4 + BigQuery
- Looker / Metabase / Hex
- Figma
- Webflow / Unbounce (for LP tests)
- SQL + dbt (read access)

## Reporting structure
Reports to the Head of Growth, VP Marketing, or directly to a PLG-focused founder. Works daily with Product Managers (in-product experiments), Engineering (feature flags, instrumentation), Data (metric definitions, warehouse), and Lifecycle/Paid marketing on cross-funnel tests.

## Success metrics (KPIs)
- Activation rate (product-specific aha-moment metric) quarter-over-quarter.
- Day-7, Day-30, and Day-90 retention by cohort.
- Experiment velocity (shipped tests per quarter) and experiment win rate.
- CAC payback period and LTV:CAC ratio against business target.
- Lifecycle-driven revenue (activation flow conversion, reactivation recovery rate).
- Viral coefficient or referral-driven acquisition share (where applicable).

Frequently asked questions

What does a Growth Marketer do day-to-day?

A Growth Marketer runs structured experimentation across the AARRR funnel: acquisition, activation, retention, referral, revenue. Partners with product and engineering on in-product tests behind feature flags, instruments events in Mixpanel/Amplitude/PostHog, prioritizes experiments via ICE/PIE, runs proper A/B tests with power analysis, and is accountable for moving activation rate, retention cohorts, and CAC payback — not for executing any one channel.

How many years of experience should a mid-level Growth Marketer have?

A mid-level Growth Marketer typically has 4-6 years of experience. At that level they should own a funnel stage (activation or retention or acquisition) with experiment velocity accountability.

Which KPIs should I hold a Growth Marketer accountable to?

The most important KPIs for a Growth Marketer are: Activation rate (product-specific aha-moment metric) quarter-over-quarter.; Day-7, Day-30, and Day-90 retention by cohort.; Experiment velocity (shipped tests per quarter) and experiment win rate.; CAC payback period and LTV:CAC ratio against business target..

What is the difference between a growth marketer and a digital marketing manager?

Digital marketing managers own channels and budget allocation across SEO, paid, email, and content. Growth marketers own experiments across the full funnel, including in-product work that marketing managers usually cannot touch. A growth marketer will ship an onboarding checklist change with the engineering team, run an activation test in Mixpanel, build a reactivation email flow in Customer.io, and launch a landing page test, all in the same week. If your bottleneck is paid channel performance, hire a digital marketing manager. If your bottleneck is activation or retention, hire a growth marketer.

How do they work with engineers on in-product growth experiments?

They ship in small, testable increments. Standard pattern is to write a short brief with hypothesis, design mocks, event tracking plan, and metric up front. Engineering puts the change behind a feature flag, growth defines the exposure and traffic split in Statsig or GrowthBook, and the test runs for long enough to reach the sample size defined in the power analysis. Growth marketers in our network are comfortable writing SQL to slice results and can push back when engineering shortcuts the instrumentation in a way that would break the read.

Related

Written by Syed Ali

Founder, Remoteria

Syed Ali founded Remoteria after a decade building distributed teams across 4 continents. He has helped 500+ companies source, vet, onboard, and scale pre-vetted offshore talent in engineering, design, marketing, and operations.

  • • 10+ years building distributed remote teams
  • • 500+ successful offshore placements across US, UK, EU, and APAC
  • • Specialist in offshore vetting and cross-timezone team integration
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Last updated: April 12, 2026