Lead Decision Scientist – Web

Life360

Lead Decision Scientist leading analytical narratives and insights at Life360. Working with AI and data to impact product strategies and user experience across teams.

Posted 7/14/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $133,000 - $195,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in web analytics and data-driven decision-making, with a strong focus on causal inference methods and experimentation to enhance user experience and conversion rates. Proficient in leveraging analytics tools and data engineering to inform product and marketing strategies.

Highest-signal resume keywords

Causal Inference MethodsGoogle Analytics 4 (GA4)SQL ProficiencyPython/R for Statistical AnalysisA/B Testing Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Causal InferenceStatistical AnalysisData AnalysisWeb AnalyticsExperimentationData EngineeringUser Experience EvaluationConversion Rate OptimizationDashboard DevelopmentConsumer Behavior Analysis

Soft Skills

Strategic ThinkingStorytellingCross-Functional CollaborationCommunicationInfluencing

Tools & Technologies

Google AnalyticsBigQueryDatabricksStatsigOptimizelyAdobe Analytics

Industry Keywords

ECommerceDigital MarketingConsumer ProductData ScienceDecision Science

Tech Stack

Tools & technologies

BigQueryPythonSQL

About the role

Key responsibilities & impact

Be the strategic thought partner for cross-functional teams (DTC, web PMs, web engineers, marketing, finance). You architect and evangelize the web analytics roadmaps, and you notice the gap between what the data shows and what the team assumes.
Tell stories that move teams to act. You diagnose and evaluate full-funnel user experiences—from initial traffic acquisition across marketing channels down to each web conversion funnel Identify drop-offs, trends, and opportunities for improved user flow and conversion rate. 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. Act as the partner for DTC and product teams to scale an agile, statistically sound multivariate experimentation program. You work with engineering to implement event instrumentation and with DTC to translate insights into action to improve web metrics and conversion
Work backward from an understanding of how users experience our website to develop and implement metrics strategies that measure what matters to our users and our business.
Conduct in-dept analysis of consumer behavior to uncover trends and preferences across cohorts, providing actionable insights to inform marketing, merchandising, and product strategies.
Experiments: Work closely with CRO and PM to improve site conversions through extensive A/B testing focused on product pages, checkout, upsells, and merchandising tactics.
Data Ownership: Stitch backend data from various data platforms (Google Analytics, BigQuery, Databricks) and build the eCommerce data pipelines with Data Engineering that support all DTC reporting.
Oversee the analysis of eCommerce KPIs, customer behavior, and digital marketing metrics. Develop and refine dashboards to provide visibility into online performance and identify optimization opportunities.
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.
Develop and communicate a clear vision for self-service and operational reporting using industry leading tools and best practices.
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.

Requirements

What you’ll need

6+ years in an analytics, data science, or decision science role at a consumer product company
Advanced degree (bachelor's or beyond) 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 Google Analytics 4 (GA4) and/or Adobe Analytics a must
Experience with Data Engineering to ingest web event streams into a centralized data environment
Proficiency in SQL and Python/R for statistical analysis

Benefits

Comp & perks

Competitive pay and benefits.
Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.
401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
Employee Assistance Program (EAP) for mental wellness.
Flexible PTO and 12 company wide days off throughout the year.
Winter and Summer Weeklong Synchronized Company Shutdowns
Learning & Development programs.
Equipment, tools, and reimbursement support for a productive remote environment.
Free Life360 Platinum Membership for your preferred circle.
Free Tile Products