Growth Engineer

Job Description - Growth Engineer

We are seeking an experienced Growth Engineer to join a dedicated task force testing a new customer experience concept against the current templated baseline. You'll own experiment velocity end-to-end: designing tests, instrumenting behavior, shipping variations, and analyzing results - blending technical execution with marketing intuition and behavioral insight.
This is a hands-on, code-shipping role embedded in a product squad. You'll collaborate with product, engineering, data science, and design daily. Your north star: measurable conversion lift on trip transactions and revenue per trip through rapid, rigorous experimentation across messaging touchpoints.

What success looks like:
- Experiment velocity: Dozens of tests designed, shipped, and conclusively measured within the task force window, with clear learnings from both wins and losses.
- Measurable lift: 2-3 mechanics identified that demonstrably move trip completion rate or revenue per trip, validated at statistical significance.
- Instrumentation coverage: Full behavioral funnel visibility from message open through downstream booking action, including cross-vertical attach rate.
- Playbook delivery: A documented, reusable set of experiment results and growth mechanics the squad can carry forward beyond the task force.

Key Responsibilities
- Experimentation & Optimization
- Design and run rapid A/B and multivariate experiments across messaging touchpoints (email, push)
- Build and maintain an experiment backlog prioritized by expected impact, cost, and learning value
- Analyze results rigorously: statistical significance, segment effects, downstream conversion - not just opens and clicks
- Instrumentation & Measurement
- Instrument user behavior end-to-end: message interaction through to booking action, cross-vertical attach, and revenue attribution
- Define and track experiment-level KPIs aligned with squad north stars (trip completion rate, revenue per trip)
- Build lightweight dashboards and alerting to surface experiment health and early signals
- Technical Execution
- Ship working variations yourself: messaging templates, personalization logic, behavioral triggers, copy and creative variants

- Build lightweight tooling and automations to accelerate experiment cycles (scripting, data pipelines, workflow glue)
- Leverage AI/LLM tools aggressively for ideation, copy generation, audience segmentation, data analysis, and workflow automation
- Cross-Functional Enablement
- Product & design: Translate behavioral insights into testable hypotheses and product recommendations
- Data science/analytics: Partner on experiment design, power calculations, causal inference, and metric definitions
- Marketing & CRM: Close feedback loops between experiment results and messaging strategy

What We're Looking For
- Growth engineering or growth marketing experience (typically 3+ years) delivering measurable acquisition or conversion improvements at scale in a product-led environment
- Technical fluency: ability to ship working code (Python, JavaScript, SQL at minimum) - you've built scrapers, internal tools, automations, or experiment infrastructure, not just configured third-party platforms
- Strong fluency in experimentation methodology: statistical significance, sample sizing, segmentation, and the difference between a metric moving and a metric mattering
- Hands-on comfort with SQL and modern data stacks; ability to self-serve analytically without waiting for a data team
- Understanding of user psychology and behavioral economics - you think in terms of motivation, friction, and timing, not just channels and templates
- Demonstrated AI-native workflow: active use of LLMs, copilots, and generative tools as daily multipliers, with informed opinions on where they help and where they don't
- Experience with messaging/CRM systems at scale and familiarity with deliverability, personalization, and lifecycle orchestration
- Exposure to multi-vertical or cross-sell environments where success means driving composite value, not single-product conversion
- Background collaborating with product and data science teams to operationalize signal feedback loops between user behavior and messaging strategy
- Excellent stakeholder communication across product, engineering, marketing, and analytics; bias toward shipping over planning

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