Senior Decision Scientist, Core Experiences

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 102.4 million monthly active users (MAU), as of June 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.

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.

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.

We're hiring a Senior Decision Scientist to be a strategic partner embedded with product and engineering teams. Someone who shapes what gets built, how we grow, and where we invest. You'll own the analytical narrative for your area and deliver insights that directly change roadmaps and resource allocation. The output is decisions, not dashboards. 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, data scientists, and ML engineers.

The US-based salary range for this position is $106,500 to $195,500 USD. 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. 

• →Be the strategic thought partner for cross-functional teams (PMs, engineers, marketing, finance). You understand the roadmaps and users, and you notice the gap between what the data shows and what the team assumes.
• →Tell stories that move teams to act. You'll present to leadership and working teams with clear narratives and a point of view. A great insight that nobody acts on is a failed insight.
• →Establish causality with the right tools for the situation, including A/B testing, analytics, and causal inference. You work with engineering to implement event instrumentation and with Product to translate insights into action.
• →Work backward from an understanding of how users experience our product to develop and implement metrics strategies that measure what matters to our users and our business. This enables a deep understanding of our users and their motivation, in a complex ecosystem with multi-user engagement and many ways to interact with our product. 
• →Build explanations on top of measurement that tie what users do to why they do it.
• →Use AI to multiply your impact. You'll use coding agents and automated analysis daily, and help shape what our AI-native analytics stack looks like, contributing to how we move from reactive to proactive to autonomous.

• Problem-solving mindset: You structure ambiguous problems precisely before reaching for a tool, AI or otherwise
• Ownership mentality: You take responsibility for your work from framing the question through delivering the recommendation and tracking its impact
• AI-native working style: You use AI tooling (Claude Code or equivalent) as a genuine development partner: delegating discrete tasks, reviewing outputs critically, and running parallel workstreams
• Curiosity and initiative: You ask whether the product is making people’s lives meaningfully better, not just whether a feature moved a metric

• 5+ years in an analytics, data science, or decision science role at a consumer tech company
• Advanced degree in a quantitative field (economics, statistics, quantitative social science, operations research) or equivalent practical experience
• Demonstrated experience with causal inference methods in applied settings (e.g., difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, propensity score matching)
• Track record of influencing product or business strategy through data, with specific examples of cross-functional impact
• Experience with experimentation platforms (Statsig, Optimizely, or similar)
• Proficiency in SQL and Python/R for statistical analysis

• Familiarity with growth experimentation design in networked or social contexts
• Experience building dbt models or contributing to analytics engineering workflows
• Experience with retention analytics driven by a high quality product experience 
• Experience with subscription or freemium business models 

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