Senior Product Analyst
New
US remote or Canada remoteFull-TimeSenior
Salary140,000 - 165,000 USD per year
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Job Details
- Experience
- 4+ years
- Required Skills
- PythonSQLTableauProduct AnalyticsData visualizationA/B testingR
Requirements
- 4+ years of experience in Product Analytics, Data Science, or a closely related analytical role within a consumer tech environment.
- Proven experience designing and analyzing A/B tests that have driven measurable improvements in core business metrics such as revenue, retention, or ARPU.
- Strong understanding of experimental design, statistics, and causal inference, including common real-world pitfalls and trade-offs.
- Expertise in analyzing user funnels, cohorts, lifecycle metrics, and end-to-end customer journeys.
- Advanced SQL skills and proficiency in Python or R for data analysis and modeling.
- Experience building dashboards and data visualizations (Tableau or similar tools is a plus).
- Strong business acumen with the ability to connect data insights to product and revenue outcomes.
- Excellent communication skills with a demonstrated ability to influence product decisions through data storytelling.
- Comfortable working in fast-paced, high-growth environments with shifting priorities.
- Ability to manage multiple analytical projects simultaneously while maintaining rigor and attention to detail.
- Experience with AI-assisted analytics tools and a willingness to adopt new technologies to enhance productivity.
Responsibilities
- Own end-to-end product analytics for key consumer-facing products, translating complex datasets into clear insights that guide product and business decisions.
- Design, execute, and analyze A/B and multivariate experiments to evaluate product features, UX changes, pricing strategies, and growth initiatives.
- Conduct deep-dive analyses on user behavior, funnels, cohorts, and lifecycle journeys to identify opportunities for growth and improved retention.
- Partner with Product Managers to define hypotheses, success metrics, guardrails, and measurement frameworks for experiments and launches.
- Build, maintain, and optimize dashboards and KPIs to monitor product performance and experiment outcomes in real time.
- Ensure accurate event tracking, instrumentation, and data integrity across new and existing product features.
- Translate complex analytical findings into clear, actionable recommendations for both technical and non-technical stakeholders.
- Support strategic deep-dives and ad-hoc analyses that influence roadmap prioritization and long-term business strategy.
- Leverage advanced analytical methods, including segmentation and propensity modeling, to enhance decision-making and uncover deeper insights.
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