Director of Data Science

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app and Tile tracking devices empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 70 million monthly active users (MAU) as of August 2024, across more than 150 countries. 

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends that basically are family). 

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above. 

About the Job

We are seeking a Director of Data Science to lead the development and integration of AI, machine learning, and data science capabilities across Life360’s diverse product and business domains. This leader will partner with teams spanning core product, user experience, international and domestic growth, ads, marketing, finance, and user acquisition to identify high-impact opportunities where intelligent systems and scientific methods can enhance decision-making and unlock new value. The role will be instrumental in shaping a cross-functional roadmap that embeds AI/ML thinking into every stage of the product and business lifecycle, empowering teams to accelerate innovation, personalize experiences, and scale operational excellence.

You will be responsible for leading a world-class team of scientists focused on building next-generation machine learning systems, deploying AI to personalize user journeys, and high-impact experimentation and causal inference. This role is perfect for a visionary leader passionate about shaping the future of AI-enabled growth in consumer mobile products.

For candidates based in the US, the salary range for this position is $213,500 to 313,500 USD. For candidates based out of Canada, the salary range for this position is $250,500 to $294,500 CAD. We take into consideration an individual's background and experience in determining final salary- therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

What You’ll Do

AI/ML-Driven Growth Innovation

• Lead the enterprise strategy for embedding AI and ML across the full customer lifecycle—from acquisition and onboarding to engagement, monetization, and retention—transforming how the business personalizes experiences, predicts behavior, and drives long-term value.
• 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. These systems serve as foundational infrastructure for continuously optimizing user experience, pricing, and content delivery across touchpoints.
• Drive cross-functional alignment with engineering, product, and marketing to productionize ML capabilities that personalize every stage of the customer journey—from initial exposure through subscription experiences to ongoing engagement and reactivation—maximizing both user satisfaction and business impact.
• Establish an enterprise-wide experimentation strategy that integrates AI-first methods, including causal inference, uplift modeling, inverse propensity scoring, and synthetic controls—unlocking more granular insights, accelerating learning cycles, and driving confident decision-making at scale.
• Act as a thought leader in data-driven growth and customer intelligence, translating technical innovation into strategic advantage while scaling organizational maturity in machine learning adoption and responsible AI use.

Data Science & Experimentation Leadership

• Causal inference & uplift modeling: Go beyond average treatment effects to model heterogeneous effects and counterfactual outcomes
• Experimentation at scale: Develop adaptive experiment designs (e.g., multi-armed bandits, Bayesian optimization) to learn faster and allocate traffic dynamically.
• Synthetic experiments: Use observational techniques