Staff Decision Scientist, Life360

• Problem-solving mindset: You structure ambiguous problems precisely before reaching for a tool, AI or otherwise
• Ownership mentality: You take responsibility from framing the question through delivering the recommendation and tracking its impact. You're accountable for decisions changed, not analyses delivered
• 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 don't wait for the roadmap to tell you what to analyze. You dig into data because you're genuinely curious about how things work
• Influence at scale: You've shaped strategy at the business unit level by framing the right question and making the evidence impossible to ignore
• Even if you don’t meet 100% of the below qualifications, you should still seriously consider applying!

Desirable

• We're hiring a Staff Decision Scientist to be strategic partners embedded with product, engineering, marketing, and finance teams
• People who shape 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. 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
• His 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
• Own the analytical narrative for your Operating Group (OG). Be the strategic thought partner across cross-functional teams (PMs, engineers, marketing, finance). You understand the roadmaps and users, and you set the agenda for the highest-leverage questions the OG should be asking
• 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
• Define metrics strategies that measure what matters. Work backward from how users experience the product to develop and implement the measurement frameworks for your OG, in a complex ecosystem with multi-user engagement and many ways to interact with the product
• 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
• Shape the AI-native analytics stack. Lead evaluation and adoption of new tools, agent workflows, and practices that enable self-serve across the OG and move the team from reactive to proactive to autonomous
• Mentor senior ICs on causal thinking, experimental rigor, and AI-leveraged workflows. Raise the ceiling of the craft