Senior actuarial advisor commercializing predictive modeling and advanced analytics for Desjardins insurance pricing. Deploying innovative capabilities across Personal and Commercial Insurance.
About the role
- Lead Data Scientist building production ML for Life360’s family safety and tracking products. Driving revenue experimentation, personalization, advertising, and subscription growth.
Responsibilities
- 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
- 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
- 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)
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