Staff Decision Scientist, Direct Revenue (AI Native)

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), as of September 30, 2026, across more than 180 countries. Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family). Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com . 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) regardless of any specified location above. 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 No other team at Life360 touches every product decision, every experiment, and every revenue lever. 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. Your analysis will go straight to the people making those calls, and you'll be in the room when they're made. That means more than answering the questions you're given. You'll reframe the ones that are off, push back when the evidence points somewhere leadership doesn't want to go, and set honest expectations about what the data can and can't tell us. You'll also be a senior voice on the team, mentoring Decision Scientists and raising the bar for how we tell stories with data across the org. 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. For candidates based in the US, the salary range for this position is $118,500 to $218,500 USD. For candidates based out of Canada, the salary range for this position is 164,000 to 193,500 CAD. We take into consideration an individual's background, job-related knowledge, skills, and experience in determining final salary. Base pay may also vary based on geographic location, with US work locations falling into one of three geographic tiers. Total compensation is inclusive of equity compensation in the form of Restricted Stock Units (RSUs) , as well as a comprehensive benefits package, including medical, dental, vision, financial, and other benefits. What You’ll Do • Be leadership's thought partner on monetization. Work directly with the executives who own subscription revenue. Bring them a point of view on where the next dollar of revenue comes from, and the evidence to back it. • Shape how we package, price, and sell membership. Lead analysis on tiers, pricing, paywalls, trials, and upgrade and downgrade paths, balancing near-term revenue against long-term member value. • Size and test new revenue opportunities. Build the case for (or against) new offerings and bundles across the app (Tile, Pet GPS, etc.) from first sizing through test design and post-launch read. • Guide international expansion. Help decide which markets to prioritize and how to adapt pricing and packaging by market, using local willingness-to-pay, conversion, and retention data. • Tell stories that change decisions. Turn complex analysis into a clear narrative with a recommendation. A great insight that nobody acts on is a failed insight. • Go beyond predictive correlation to causation. Use A/B tests, pricing experiments, and causal inference to measure what actually moves conversion, retention, and LTV. • Shape the AI-native analytics stack. Lead adoption of tools and agent workflows that make monetization analysis faster and more self-serve, so the team spends its time on judgment, not plumbing. • Push back and manage expectations. Say no to the wrong question, reset unrealistic targets with data, and keep stakeholders aligned on what we know, what we don't, and what it'll take to find out. • Mentor and multiply. Coach Decision Scientists on framing, causal rigor, and executive communication. Review their work, help th