Lead Decision Scientist (International)

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 97.8 million monthly active users (MAU), as of March 31, 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.

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 Lead Decision Scientist to be strategic partners embedded with product, engineering, marketing, and finance teams. 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. You’ll also help make the AI‑native organization a reality, shaping the tools and workflows that let automation take on more so the team can go deeper. 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. This role is based in Central London with a hybrid model of remote and in person/office meetings. The UK-based salary range for this position is £89,500 - 105,000 with an additional equity grant. We take into consideration an individual's background and experience in determining final salary – therefore, base pay offered may vary considerably depending on job‑related knowledge, skills, and experience.

What You’ll Do

• 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.
• Establish causality with the right tools for the situation, including A/B testing, analytics, and causal inference.
• 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.
• Build explanations on top of measurement, always grounding analysis in the reality that users are people with motivations and context the data alone won’t tell you.
• 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.

Core Expectations

• 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.
• Curiosity and initiative: You don’t wait for the roadmap to tell you what to analyze.

Desired Experience & Qualifications

• 6+ 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.
• Track record of influencing product or business strategy through data.
• Experience with experimentation platforms (Statsig, Optimizely, or similar).
• Proficiency in SQL and Python/R for statistical analysis.

Preferred Qualifications

• Experience with subscription or freemium business models.
• Familiarity with international / multi‑market analytics.
• Experience building dbt models or contributing to analytics engineering workflows.
• Background in growth, retention, or lifecycle analytics.
• Experience with LTV modeling, incrementality testing, or marketing mix modeling.

Life360 Values

• Be a Good Person – We have a team of high integrity people you can trust.
• Be Direct With Respect – We communicate directly, even when it’s hard.
• Members Before Metrics – We focus on building an exceptional experience for families.
• High Intensity, High Impact – We do whatever it takes to get the job done.

Our Commitment to Diversity

We believe that different ideas, perspectives and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status. We encourage people of all backgrounds to apply.