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# Lead Decision Scientist

- **Company:** Life360
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $133,000.0 - $195,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Python (Programming Language), SQL Databases, Optimizely
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/lead-decision-scientist-product-life360-8051670

## About the Role

* 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 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., * 6+ years in an analytics, data science, or decision science role at a consumer tech company
 * Bachelor's degree in a quantitative field (economics, statistics, quantitative social science, operations research)
 * 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, * 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

## Description

* 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, 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, contributing to how we move from reactive to proactive to autonomous.


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