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Life360

Staff Decision Scientist, Direct Revenue – AI Native

Life360

. Act as leadership's thought partner on monetization and subscription revenue .

Posted 11/10/2026full-timeRemote • United States, CanadaLead💰 $118,500 - $218,500 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in subscription monetization strategies, including pricing, packaging, and conversion analysis, while leveraging advanced analytical methods and AI-native tools to drive revenue growth. Proven ability to communicate complex data insights effectively to executives and mentor teams in decision science.

Highest-signal resume keywords
Subscription MonetizationCausal Inference MethodsSQL ProficiencyPython/R ProficiencyExecutive Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Causal InferencePricing AnalysisA/B TestingLTV ModelingStatistical Analysis
Soft Skills
StorytellingStakeholder JudgmentMentorshipCritical ThinkingExecutive Presence
Tools & Technologies
StatsigOptimizelyClaude CodeAI Tools for SQLAI Tools for Python/R
Industry Keywords
Consumer TechMonetization AnalyticsFreemium ModelsMulti-Tier SubscriptionInternational Pricing

Tech Stack

Tools & technologies
PythonSQL

About the role

Key responsibilities & impact
  • Act as leadership's thought partner on monetization and subscription revenue
  • Advise executives on where the next dollar of revenue comes from using evidence-based analysis
  • Shape membership packaging, pricing, paywalls, trials, and upgrade/downgrade paths
  • Analyze tiers, pricing, and long-term member value
  • Size and test new revenue opportunities and bundles across the app, Tile, and Pet GPS
  • Design tests and conduct post-launch analysis
  • Guide international expansion by prioritizing markets and adapting pricing and packaging
  • Translate willingness-to-pay, conversion, and retention data into recommendations
  • Turn complex analysis into clear narratives that change decisions
  • Apply A/B testing, pricing experiments, and causal inference to measure conversion, retention, and LTV
  • Lead adoption of AI-native analytics tools and agent workflows
  • Improve self-service monetization analysis and team velocity
  • Push back on incorrect questions and unrealistic targets
  • Align stakeholders on knowns, unknowns, and required research
  • Mentor Decision Scientists on framing, causal rigor, and executive communication
  • Review work and help prepare leadership readouts
  • Report to the Data & Analytics leadership team
  • Collaborate with data engineers, analytics engineers, data scientists, and ML engineers

Requirements

What you’ll need
  • 8+ years in an analytics, data science, or decision science role at a consumer tech company
  • Direct experience with subscription monetization: pricing, packaging, paywalls, conversion, or churn
  • Advanced degree in a quantitative field or equivalent practical experience
  • Demonstrated experience with causal inference methods in applied settings, including difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, and propensity score matching
  • Track record of partnering with executives and influencing major revenue or strategy decisions
  • Experience designing and analyzing pricing or monetization experiments using Statsig, Optimizely, or similar
  • Experience formally or informally mentoring analysts or data scientists
  • Proficiency in SQL and Python/R for statistical analysis
  • Executive presence and ability to handle challenging questions
  • Storytelling and clear communication tailored to different audiences
  • Ability to push back on leadership respectfully using data
  • Stakeholder judgment and ability to set realistic expectations
  • Ownership from question framing through recommendation and impact tracking
  • Commitment to mentorship
  • AI-native working style using Claude Code or equivalent
  • Daily use of AI tools for SQL, Python/R analysis, experiment readouts, and leadership memos
  • Critical review of AI outputs, queries, statistical assumptions, and causal claims
  • Continuous learning about experimentation, causal inference, and monetization analytics
  • Nice-to-have: experience with freemium or multi-tier subscription models
  • Nice-to-have: experience with international pricing or multi-market launches
  • Nice-to-have: familiarity with pricing and marketplace analytics
  • Nice-to-have: experience building dbt models or contributing to analytics engineering workflows
  • Nice-to-have: experience with hardware-plus-subscription bundles
  • Experience with LTV modeling or willingness-to-pay research (e.g., conjoint, Van Westendorp)

Benefits

Comp & perks
  • Medical, dental, vision, life and disability insurance plans (100% paid for US employees)
  • Life, disability, and supplemental medical and dental plans for Canadian employees
  • 401(k) plan with company matching program in the US
  • RRSP with DPSP plan for Canadian employees
  • Paid parental leave
  • Mental Wellness Program & Employee Assistance Program (EAP)
  • Flexible PTO
  • Companywide holidays
  • Summer and winter shutdowns
  • Learning & Development programs
  • Equipment, tools, and reimbursement support for a productive remote environment
  • Free Life360 Platinum Membership and Tile trackers
  • Equity compensation in the form of Restricted Stock Units (RSUs)