Life360 is looking to enhance its product and business domains by integrating AI, machine learning, and data science capabilities to improve decision-making, unlock new value, accelerate innovation, personalize experiences, and scale operational excellence.
Requirements
- 10+ years in Data Science, ML, or advanced analytics roles with 5+ years of team leadership
- Track record of deploying AI/ML systems in production to drive measurable business impact
- Mastery of machine learning (e.g., classification, clustering, time series, LTV/churn models), with hands-on experience using Python, scikit-learn, XGBoost, TensorFlow/PyTorch, etc.
- Strong understanding of causal inference frameworks (e.g., RCTs, IVs, diff-in-diff, matching) and their application to B2C growth
- Deep experimentation expertise, including experience running A/B/n, multi-variate, and sequential tests at scale
- Advanced degree (MS/PhD) in Statistics, Machine Learning, Computer Science, or related discipline
- Experience building personalized recommendation or dynamic decision systems in consumer tech
Responsibilities
- Lead the enterprise strategy for embedding AI and ML across the full customer lifecycle—from acquisition and onboarding to engagement, monetization, and retention
- Define and scale intelligent decision systems that power dynamic, real-time interactions using advanced frameworks such as reinforcement learning, multi-armed bandits, and recommender systems
- Drive cross-functional alignment with engineering, product, and marketing to productionize ML capabilities that personalize every stage of the customer journey
- Establish an enterprise-wide experimentation strategy that integrates AI-first methods, including causal inference, uplift modeling, inverse propensity scoring, and synthetic controls
- Go beyond average treatment effects to model heterogeneous effects and counterfactual outcomes
- Develop adaptive experiment designs (e.g., multi-armed bandits, Bayesian optimization) to learn faster and allocate traffic dynamically
- Use observational techniques (e.g., inverse propensity scoring, matching, synthetic controls) when randomized testing isn't possible
Other
- Lead the development and integration of AI, machine learning, and data science capabilities across Life360's diverse product and business domains.
- Partner with teams spanning core product, user experience, international and domestic growth, ads, marketing, finance, and user acquisition to identify high-impact opportunities
- Act as a thought leader in data-driven growth and customer intelligence, translating technical innovation into strategic advantage
- Build and mentor a high-performing team of ML scientists, statisticians, and growth analysts.
- Serve as a cross-functional thought partner to Product, Marketing, Engineering, and Lifecycle teams.
