Senior Product Analyst

New

JobgetherFinancial technology

Based in the United StatesFull-TimeSenior

Salary140,000 - 165,000 USD per year

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Job Details

Experience: At least 4 years of experience in data science, product analytics, or a related role within a consumer-facing technology company.
Required Skills: PythonSQLMachine LearningTableauProduct AnalyticsA/B testingR

Have at least 4 years of experience in data science, product analytics, or a related role within a consumer-facing technology company.
Demonstrate experience designing and analyzing A/B tests that produced measurable improvements in revenue, ARPU, retention, or other key business metrics.
Understand experimental design, statistics, and causal inference, including the limitations and trade-offs of real-world experimentation.
Have extensive experience analyzing conversion funnels, cohorts, lifecycle metrics, and customer journeys.
Have advanced SQL skills and proficiency in Python or R.
Have experience creating dashboards and data visualizations; Tableau experience is an advantage.
Be able to use AI tools to expand analytical capabilities and independently tackle complex analytical questions.
Connect data insights with product strategy and commercial outcomes.
Communicate and manage stakeholders effectively, influencing decisions through evidence-based recommendations.
Have experience working in a fast-paced, high-growth startup environment.
Manage multiple initiatives while maintaining analytical rigor and execution quality.

Own end-to-end product analytics for key consumer-facing products and strategic initiatives.
Analyze user behavior, conversion funnels, cohorts, and customer journeys to identify opportunities for growth, monetization, retention, and improved user experience.
Design, execute, and evaluate A/B and multivariate experiments across product features, user experience, pricing, and growth initiatives.
Collaborate with Product Managers to establish hypotheses, success metrics, and guardrails for experiments and product launches.
Translate analytical findings into actionable recommendations for technical and non-technical stakeholders.
Develop and maintain product KPIs, dashboards, and monitoring metrics.
Ensure accurate event tracking and reliable data instrumentation for product features.
Use AI-assisted tools and machine learning techniques, including segmentation and propensity scoring, to support analysis and product decisions.
Conduct ad hoc analyses and strategic analyses that inform roadmap prioritization and business strategy.

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