Senior Data Scientist, Product Analytics
New
Remote-first team... Canadian remote locations... U.S. remote locationsFull-TimeSenior
Salary150,000 CAD - 195,000 USD per year
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Job Details
- Experience
- 4+ years
- Required Skills
- PythonSQLMachine LearningTableauProduct AnalyticsA/B testingR
Requirements
- 4+ years of experience in Data Science, Product Analytics, or a closely related role in a consumer-facing tech company.
- Proven, hands-on experience designing and analyzing A/B tests that led to measurable improvements in business metrics.
- Strong understanding of experimental design, statistics, and causal inference.
- Deep experience analyzing user funnels, cohorts, lifecycle metrics, and customer journeys.
- Fluency in SQL and proficiency in Python or R.
- Experience building compelling dashboards and data visualizations.
- Ability to leverage AI tools to extend analytical capabilities.
- Strong business acumen with the ability to connect data insights to product strategy and commercial outcomes.
- Excellent communication skills with the ability to influence product decisions through data.
- Experience working in a fast-paced, high-growth startup environment.
- Ability to manage multiple initiatives simultaneously while maintaining analytical rigor.
Responsibilities
- Own and drive end-to-end product analytics for key consumer-facing products and initiatives.
- Conduct deep-dive analysis on user behavior, funnels, cohorts, and journeys to identify opportunities for growth, monetization, and improved user experience.
- Design, execute, and analyze A/B and multivariate experiments to evaluate product, UX, pricing, and growth initiatives.
- Partner with Product Managers to define clear hypotheses, success metrics, and guardrails for experiments and product launches.
- Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders.
- Develop and maintain key product KPIs, dashboards, and monitoring metrics.
- Ensure accurate event tracking and data instrumentation for new and existing product features.
- Leverage AI-assisted tools and ML techniques to support product decisions.
- Support strategic deep dives that influence roadmap prioritization and business strategy.
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