Lead Data Scientist

Life360

. Investigate revenue-generating opportunities and data, and use findings to size, scope, and measure product changes in Databricks .

Posted 10/7/2026full-timeRemote • United States, CanadaSenior💰 $175,000 - $218,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production ML systems, utilizing advanced statistical analysis and causal inference techniques. Proficient in collaborating with cross-functional teams to integrate ML solutions and improve data ecosystems while mentoring data scientists in best practices.

Highest-signal resume keywords

Machine Learning System DevelopmentPython ProgrammingCausal Inference TechniquesData Transformation and InstrumentationProject Leadership and Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical AnalysisCausal Inference ProgrammingData EngineeringExperiment DesignMonitoring and AnalysisML Model Registry ManagementFeature Store ManagementData Pipeline ImprovementAI Tool Utilization

Soft Skills

Strong CommunicationProject LeadershipInfluencing Cross-Functional TeamsStructured Problem SolvingMentoring

Tools & Technologies

DatabricksPythonScikit-learnPySparkClaude CodeML Feature Monitoring ToolsVersion Control SystemsConsumer Technology Experimentation ToolsAI WorkflowsDigital Advertising Infrastructure

Certifications & Qualifications

Advanced Degree in Statistical Analysis or Related Field

Industry Keywords

B2C TechnologyGeospatial DataMobile Location-Based ServicesSubscription ProductsLifecycle MarketingUser AcquisitionAd Tech InfrastructureRanking AlgorithmsGrouping AlgorithmsRevenue Reporting

Tech Stack

Tools & technologies

CloudPySparkPythonScikit-Learn

About the role

Key responsibilities & impact

Investigate revenue-generating opportunities and data, and use findings to size, scope, and measure product changes in Databricks
Design, build, deploy, and operate production ML systems, including batch inference, online services, and online learning models
Use the team’s feature store and model registry for personalization, experimentation, and automation use cases
Partner with Product, Mobile Engineering, Cloud Engineering, Data Engineering, and MLOps to integrate ML systems into user-facing features
Set up monitoring to measure ML feature performance and business impact
Implement lineage tracking for data, code, and model artifacts to keep the ML lifecycle compliant, reproducible, and secure
Improve the data ecosystem and pipelines supporting experimentation and ML
Mentor data scientists and define best practices for advanced analytics and ML system development
Use Claude Code and other AI tools across data discovery, modeling, and experiment evaluation
Help scale production ML delivery and shape the team roadmap with the data science lead and product manager

Requirements

What you’ll need

Advanced degree in a field that relies on sophisticated statistical analysis or equivalent industry experience
6+ years of experience scoping, building, and analyzing ML-powered systems, including models shipped to production
Significant experience with Python, scikit-learn, PySpark, and causal inference programming languages
Familiarity with software engineering best practices, including testing, modularization, and version control
Technical training and professional experience applying modern causal inference and causal analysis techniques
Significant experience working with found data, guiding instrumentation, and implementing data transformations
Hands-on experience setting up consumer technology experiments, including experiment design, monitoring, and analysis
Experience building ML or running experiments at a consumer (B2C) technology company
Strong communication and project leadership skills
Ability to influence cross-functional teams
Structured, hypothesis-driven, data-supported problem solving
Prior experience leveraging LLMs in advanced data processing and analysis workflows
Preferred: experience with digital advertising and ad tech infrastructure
Preferred: experience with ranking and grouping algorithms for content feeds
Preferred: experience managing production feature stores and ML model registries
Preferred: experience working with product line GMs, revenue reporting, and forecasting analyses
Preferred: experience with subscription products, lifecycle marketing, or user acquisition
Preferred: experience with geospatial data and mobile location-based services
AI fluency, critical review of AI-generated code and models, and accountability for shipped work
Ability to run parallel AI-assisted workstreams and share AI workflows with the team
Continuous learning about new AI tools and techniques

Benefits

Comp & perks

Medical, dental, vision, life and disability insurance plans (100% paid for US employees)
Life and disability insurance and supplemental medical and dental plans for Canadian employees
401(k) plan with company matching program in the US
RRSP with DPSP plan for Canadian employees
Paid parental leave
Mental Wellness Program & Employee Assistance Program (EAP)
Flexible PTO
Companywide holidays
Summer and winter shutdowns
Learning & Development programs
Equipment, tools, and reimbursement support for a productive remote environment
Free Life360 Platinum Membership and Tile trackers
Equity compensation in the form of Restricted Stock Units (RSUs)