Staff Decision Scientist, Direct Revenue (AI Native) - Life360

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 107.7 million monthly active users (MAU) across more than 180 countries.

Life360 has more than 500 (and growing!) remote-first employees. Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely within the US and Canada.

We are AI Native

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.

Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

Data & Analytics is a 60+ person organization spanning data engineering, analytics engineering, data science, and ML. We're building it to be AI-native, where automation handles the volume so our people can focus on understanding why users behave the way they do, establishing what actually causes what, and turning those findings into action.

About the Job

Tens of millions of families use Life360 every month. Turning that trust into a durable subscription business, without breaking what makes members love the product, is one of the most consequential problems at the company. This role sits at the center of it.

As the Staff Decision Scientist for Direct Revenue, you'll be the analytical partner to the leaders who run our subscription business. You'll work on the questions that set the direction of the company: how we package and price membership, which new offerings are worth building, where and how we expand internationally, and what drives a member to subscribe, stay, or leave.

This is not a production ML role (we have a dedicated Data Science / MLE team for that). Your primary tools are statistical inference, clear thinking, and the judgment to know which question matters most. You'll report into the Data & Analytics leadership team and work alongside data engineers, analytics engineers, data scientists, and ML engineers.

What You’ll Do

• Monetization Thought Partner: Work directly with executives who own subscription revenue. Bring a clear point of view on where the next dollar of revenue comes from, backed by solid evidence.
• Pricing & Packaging Strategy: Lead analysis on tiers, pricing, paywalls, trials, upgrade, and downgrade paths, balancing near-term revenue against long-term member value.
• Opportunity Sizing & Experimentation: Build cases for or against new offerings and app bundles (Tile, Pet GPS, etc.) from first sizing through test design and post-launch readouts.
• International Expansion: Help decide which markets to prioritize and adapt pricing/packaging based on local willingness-to-pay, conversion, and retention data.
• Data Storytelling: Turn complex analysis into clear narratives with concrete recommendations.
• Causal Inference over Correlation: Utilize A/B tests, pricing experiments, and causal inference methods to measure true drivers of conversion, retention, and LTV.
• AI-Native Analytics Stack: Lead adoption of AI tools and agent workflows to accelerate monetization analysis.
• Executive Alignment & Expectation Management: Reset targets with data and keep stakeholders aligned on knowns, unknowns, and required next steps.
• Mentorship: Coach Decision Scientists on analytical framing, causal rigor, and executive communication.

What We’re Looking For

Core Expectations

• Executive Presence: Credible with senior leaders, comfortable holding the room, handling hard questions in real time, and disagreeing constructively.
• Storytelling & Clarity: Lead with the answer, trim unnecessary details, and adapt messaging to diverse audiences.
• Courage to Push Back: Direct and respectful communication of data findings, even when contrary to leadership expectations.
• Ownership Mentality: End-to-end accountability from framing questions to driving decision impact.
• AI-Native Working Style: Proven use of AI tools (e.g., Claude Code or equivalent) as a genuine development partner for parallel workstreams and complex tasks.

Required Experience & Qualifications

• 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 (economics, statistics, quantitative social science, operations research) or equivalent practical experience.
• Applied experience with causal inference methods (e.g., difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, propensity score matching).
• Proven track record of partnering with executives to influence major strategy and revenue decisions.
• Experience designing and analyzing pricing or monetization experiments using platforms like Statsig or Optimizely.
• Experience formally or informally mentoring data scientists or analysts.
• Proficiency in SQL and Python/R for statistical analysis.

Nice to Have Qualifications

• Experience with freemium or multi-tier subscription models.
• Experience with international pricing or multi-market launches.
• Familiarity with pricing and marketplace analytics.
• Experience building dbt models or contributing to analytics engineering workflows.
• Experience with hardware-plus-subscription bundles.
• Experience with LTV modeling or willingness-to-pay research (conjoint, Van Westendorp).

AI-Native Expectations

• Daily Use: Utilize tools like Claude Code as working partners for SQL, Python/R analysis, experiment readouts, and draft memos.
• Judgment & Ownership: Rigorously review AI outputs for query correctness, statistical assumptions, and causal validity before sharing.
• Velocity: Leverage AI to complete opportunity sizing, test designs, and experiment readouts in days rather than weeks.
• Team Leadership: Share effective prompts, agent workflows, and review checklists to raise team-wide AI fluency.

Compensation & Benefits

• Salary Range:
  • US Candidates: $118,500 – $218,500 USD (varies by geographic tier and experience)
  • Canada Candidates: $164,000 – $193,500 CAD
• Equity: Restricted Stock Units (RSUs)
• Health Coverage: Medical, dental, vision, life, and disability insurance plans (100% company-paid for US employees; comprehensive supplemental plans for Canadian employees).
• Retirement: 401(k) matching (US) / RRSP with DPSP plan (Canada).
• Time Off: Flexible PTO, paid parental leave, companywide holidays, plus summer and winter shutdowns.
• Wellness & Support: Mental Wellness Program & Employee Assistance Program (EAP).
• Remote Setup: Equipment, tools, and reimbursement support for a productive home office environment.
• Perks: Free Life360 Platinum Membership and Tile trackers.