VP, Product, Growth Experimentation
New
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Life360Mobile consumer products
All positions, unless otherwise specified, can be performed remotely (within the US and Canada) regardless of any specified location above.Full-TimeVp
Salary not disclosed
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Job Details
- Experience
- 15+ years in consumer products; 10+ years of managing high performing teams.
- Required Skills
- Cross-functional Team LeadershipA/B testing
Requirements
- Have 15+ years of experience in consumer products.
- Bring deep, hands-on ownership of growth and experimentation at scale, ideally in a business with tens of millions of users.
- Have been accountable for moving top-line outcomes, not just shipping features.
- Have 10+ years of experience managing high-performing teams that deliver outcomes.
- Demonstrate strategic ownership in ambiguous problem spaces, including prioritization under constrained capacity and breaking strategy into shippable milestones.
- Design and defend metric frameworks, including primary metrics, driver metrics, and guardrails.
- Demonstrate deep experiment-design fluency, including power, minimum detectable effect, guardrail metrics, A/B/n testing, multi-armed bandits, holdouts, sequential-testing pitfalls, interference, network effects, and novelty effects.
- Show a track record of moving activation, engagement, or retention through a portfolio of experiments.
- Think in funnels and cohorts and distinguish incremental growth from vanity metrics or shifts between features.
- Lead cross-functionally with Engineering, Design, Data Science, and Analytics.
- Bring mobile-first consumer expertise, including how experimentation and instrumentation differ across iOS, Android, and international markets.
- Use AI daily for substantive work such as research, analysis, experiment design, prototyping, drafting, and readouts, and review AI-generated outputs with accountability.
- Build reusable AI prompts and workflows and help teammates develop their AI adoption.
Responsibilities
- Drive a high-velocity experimentation program across the full free-member funnel, from acquisition and activation through engagement and retention.
- Build hypothesis trees and prioritize experimentation capacity based on opportunities for incremental member growth.
- Select experiment methods, including A/B/n tests, multi-armed bandit optimization, and long-term holdouts, and apply statistical discipline to experiment design.
- Build reusable playbooks, templates, and standards, and partner with Data Science and Engineering to improve the experimentation platform and instrumentation.
- Produce clear experiment readouts and make defensible ship, iterate, or kill decisions.
- Build a durable record of experiment learnings and use AI across hypothesis generation, analysis, readouts, and shipped experiments.
- Protect member trust by ensuring experiments create genuine member value.
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