Growth Engineer

Details

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 will own experiment velocity end-to-end: designing tests, instrumenting behavior, shipping variations, and analyzing results while combining technical execution with marketing intuition and behavioral insight.

This is a hands-on, code-shipping role embedded in a product squad. You will collaborate daily with product, engineering, data science, and design. The focus is on achieving 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: Identify 2–3 mechanics that demonstrably move trip completion rate or revenue per trip and validate them at statistical significance.
• Instrumentation coverage: Provide full behavioral funnel visibility from message open through downstream booking action, including cross-vertical attach rate.
• Playbook delivery: Deliver a documented, reusable set of experiment results and growth mechanics that the squad can carry forward beyond the task force.

Responsibilities

Experimentation and Optimization

• Design and run rapid A/B and multivariate experiments across messaging touchpoints, including email and push.
• Build and maintain an experiment backlog prioritized by expected impact, cost, and learning value.
• Analyze results rigorously, including statistical significance, segment effects, and downstream conversion rather than only opens and clicks.

Instrumentation and Measurement

• Instrument user behavior end-to-end, from message interaction through booking action, cross-vertical attach, and revenue attribution.
• Define and track experiment-level KPIs aligned with squad north stars, including trip completion rate and revenue per trip.
• Build lightweight dashboards and alerting to surface experiment health and early signals.

Technical Execution

• Ship working variations yourself, including messaging templates, personalization logic, behavioral triggers, copy, and creative variants.
• Build lightweight tooling and automations to accelerate experiment cycles, including scripting, data pipelines, and workflow glue.
• Leverage AI and LLM tools for ideation, copy generation, audience segmentation, data analysis, and workflow automation.

Cross-Functional Enablement

• Translate behavioral insights into testable hypotheses and product recommendations in collaboration with product and design.
• Partner with data science and analytics on experiment design, power calculations, causal inference, and metric definitions.
• Close feedback loops between experiment results and messaging strategy with marketing and CRM teams.

Requirements

• Growth engineering or growth marketing experience, typically 3+ years, delivering measurable acquisition or conversion improvements at scale in a product-led environment.
• Ability to ship working code using Python, JavaScript, and SQL at minimum. Experience building scrapers, internal tools, automations, or experiment infrastructure rather than only configuring third-party platforms.
• Strong fluency in experimentation methodology, including statistical significance, sample sizing, segmentation, and distinguishing between a metric moving and a metric mattering.
• Hands-on comfort with SQL and modern data stacks, with the ability to self-serve analytically without waiting for a data team.
• Understanding of user psychology and behavioral economics, including motivation, friction, and timing.
• Demonstrated AI-native workflow, including active use of LLMs, copilots, and generative tools as daily multipliers, with informed opinions on their appropriate use.
• Experience with messaging or 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 rather than single-product conversion.
• Background collaborating with product and data science teams to operationalize feedback loops between user behavior and messaging strategy.
• Excellent stakeholder communication across product, engineering, marketing, and analytics, with a bias toward shipping over planning.