Lead Decision Scientist (Web)

What You'll Do 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. What We're Looking For 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: 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. Desired Experience & Qualifications 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 Preferred Qualifications Experience with subscription or freemium business models Familiarity with international / multi-market analytics Proficiency in Google Tag Manager (GTM) or Tealium (Server-Side deployment experience heavily preferred). Experience building dbt models or contributing to analytics engineering workflows Experience with revenue forecasting frameworks for eCommerce businesses Experience with LTV modeling, incrementality testing, or marketing mix modeling Our Benefits Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer life and disability as well as 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. Paid parental leave Mental Wellness Program & Employee Assistance Program (EAP) for mental well-being Generous time off: flexible PTO, companywide holidays throughout the year plus summer and winter shutdowns Learning & Development programs Equipment, tools, and reimbursement support for a productive remote environment. Free Life360 Platinum Membership Tile trackers Life360 Values Our company’s mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference 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 e