Lead Data Scientist, Devices

About Life
360

Life
360’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. Life
360 serves approximately 88 million monthly active users (MAU), as of June 2025 across more than 180 countries.

Life
360 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).

Life
360 has more than 500 (and growing!) remote-first employees. For more information, please visit

Life
360 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.

The mission of the data science team is to increase the value of our location-based safety solutions by optimizing and enhancing the user experience and creating new growth opportunities. As part of the product organization, we work closely with product managers, marketing, analytics, finance, engineering, and other cross-functional partners. This team is small and lean, always looking for and delivering the highest ROI.

Life
360 is seeking a Lead Data Scientist who is able to help our company grow by solving real-world problems in a fast-paced environment. Your expertise in data analysis, machine learning, and statistical modeling will drive key insights and recommendations, enhance the user experience, increase product efficiency, and continuously evolve our safety solutions. You will provide subject matter expertise and thought leadership, build relationships with key stakeholders, identify and understand opportunities (both internal and external), and develop new insights, product features, and scalable services using data from our mobile, cloud, and third-party platforms.

You’ll be a critical part of the entire project lifecycle from concept, requirements, and design to rapid prototyping, production, and hypothesis testing.

The US-based salary range for this position is $146,000 to $214,500. 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.

• Collaborate with firmware and hardware teams
• Partner with Product, Hardware, Firmware, and GTM teams to optimize data sampling, preprocessing, and inference pipelines on constrained devices
• Mentor data scientists and analysts, raising technical and business impact.
• Design experiments to collect labeled training data from real-world usage scenarios
• Focus on improving device usability and member experience through data.
• Contribute to patentable IP and long-term ML roadmap for intelligent hardware
• Embody Life
  360 values: integrity, respect, member-first, and urgency with impact.
• Research and Innovation:
  Stay up-to-date with the latest advancements in data science and machine learning, bringing innovative ideas and best practices to the team and the company.

• Bachelor’s in data science, computer science, statistics, or related field
• Proven experience (5+ years) as a Data Scientist, working on complex projects and large datasets
• Experience in ML models for time-series, signal processing, or embedded systems applications is highly desirable
• Strong background in consumer hardware/device data (telemetry, sensors, usage logs).
• Expertise in ML for personalization, anomaly detection, and predictive modeling.
• Skilled in building pipelines that operationalize device data for analytics and production ML.
• Hands-on…