Lead Decision Scientist, Product
New
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Life360Consumer Tech
All positions, unless otherwise specified, can be performed remotely (within the US and Canada) regardless of any specified location above.Full-TimeLead
SalaryFor candidates based in the US, the salary range for this position is $133,000 to $195,000 USD. For candidates based out of Canada, the salary range for this position is 147,500 to 173,000 CAD.
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonSQLProduct AnalyticsData scienceA/B testingR
Requirements
- 6+ years in an analytics, data science, or decision science role at a consumer tech company.
- Advanced degree in a quantitative field (economics, statistics, quantitative social science, operations research) or equivalent practical experience.
- Demonstrated experience with causal inference methods such as difference-in-differences, instrumental variables, and regression discontinuity.
- Proven track record of influencing product or business strategy through data-driven insights.
- Proficiency in SQL and Python or R for statistical analysis.
- Experience working with experimentation platforms like Statsig or Optimizely.
- Ability to structure ambiguous problems and maintain ownership through to recommendation and impact tracking.
- Experience using AI tooling for development tasks and parallel workstreams.
- Experience with subscription or freemium business models is preferred.
- Familiarity with international or multi-market analytics is preferred.
Responsibilities
- Partner with cross-functional teams to identify and bridge gaps between data findings and team assumptions.
- Present clear, action-oriented narratives to leadership to influence product strategy.
- Establish causality using A/B testing, analytics, and causal inference techniques.
- Develop and implement metrics strategies that reflect the user experience in a complex, multi-user ecosystem.
- Ground analytical findings in the reality of user motivations and context.
- Leverage AI tools and coding agents to multiply impact and contribute to an AI-native analytics stack.
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