Staff Decision Scientist, Advanced Analytics
New
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Life360Consumer technology
Location: Remote, USAFull-TimeStaff
SalaryFor candidates based in the US, the salary range for this position is $130,500 to $242,500 USD. For candidates based out of Canada, the salary range for this position is 180,500 to 214,000 CAD. Total compensation is inclusive of equity compensation in the form of Restricted Stock Units (RSUs).
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Job Details
- Experience
- 8+ years in an analytics, data science, or decision science role at a consumer tech company.
- Required Skills
- PythonSQLR
Requirements
- Have 8+ years of experience in analytics, data science, or decision science at a consumer tech company.
- Have an advanced degree in a quantitative field or equivalent practical experience.
- Bring deep applied experience with causal inference methods, such as difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, or propensity score matching.
- Have built and owned a forecast or growth model for a core business metric, including cohort- or component-based approaches.
- Bring expertise in experiment design and analysis at scale, including variance reduction, sequential testing, and network effects or interference.
- Have experience with experimentation platforms such as Statsig, Optimizely, or similar.
- Have a track record of setting analytical standards and mentoring other data scientists.
- Be proficient in SQL and Python or R for statistical analysis.
Responsibilities
- Build and maintain the MAU forecast and growth model in Python and SQL, track forecast accuracy, and explain forecast misses.
- Set standards for experiment design and analysis, including power, metric selection, variance reduction, sequential testing, heterogeneous effects, and interference.
- Apply quasi-experimental methods when clean experiments are not possible and make reusable approaches available to the team.
- Define and document analytical best practices and review analyses across operating groups.
- Collaborate with Decision Scientists, Data Scientists, Analytics Engineers, and Data Engineers on analytical methods and durable data models, metrics, and tooling.
- Build AI agent workflows, templates, and tools for forecasts, experiment readouts, and causal analyses.
- Mentor colleagues through analysis and code reviews, internal talks, and written guides.
- Translate forecasts and causal findings into clear recommendations for leadership.
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