Product Analyst
New
J
JobgetherProduct Analytics
Based in United StatesFull-Time
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLBusiness IntelligenceMicrosoft Power BIGoogle AnalyticsTableauA/B testingLooker
Requirements
- Proven experience as a Product Analyst, Data Analyst, or in a similar analytical role within digital products.
- Strong proficiency in SQL and experience working with large datasets.
- Hands-on experience with business intelligence platforms such as Tableau, Power BI, Looker, or equivalent tools.
- Solid understanding of product analytics, customer behavior analysis, experimentation, and A/B testing methodologies.
- Strong analytical thinking, problem-solving abilities, and exceptional attention to detail.
- Excellent communication skills with the ability to present insights clearly to both technical and non-technical audiences.
- Self-motivated, adaptable, and comfortable working in a collaborative remote environment.
- Experience with event-based analytics platforms such as Google Analytics 4, Amplitude, or Mixpanel is an advantage.
- Knowledge of digital product monetization models, customer lifecycle management, or online platform analytics is desirable.
- Experience with Python or statistical analysis tools is considered a plus.
Responsibilities
- Analyze product performance and user behavior to identify trends, opportunities, and areas for improvement.
- Define, monitor, and optimize key product metrics such as retention, conversion, lifetime value, revenue, and churn.
- Build and maintain dashboards and reporting solutions to support informed decision-making across Product, Marketing, and Operations teams.
- Conduct in-depth analyses of customer journeys, feature adoption, promotional initiatives, and overall product performance.
- Partner with Product Managers to evaluate new releases, product enhancements, and A/B testing initiatives.
- Identify friction points within the customer journey and recommend data-backed improvements.
- Collaborate with data teams to ensure the quality, consistency, and availability of analytical data.
- Translate complex analytical findings into clear, actionable recommendations for both technical and business stakeholders.
- Support customer segmentation, personalization initiatives, and market research to improve user engagement and business outcomes.
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