Data Analyst, Product
New
Based in the United StatesFull-TimeJunior
Salary$95,000 - $133,000 USD base salary range
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Job Details
- Experience
- 2+ years
- Required Skills
- SQLBusiness IntelligenceMicrosoft Power BITableauProduct AnalyticsData visualizationA/B testingLooker
Requirements
- 2+ years of experience working with data in an analytics, business intelligence, or product analytics environment.
- Working knowledge of SQL, with the ability to independently write and troubleshoot queries.
- Experience using product analytics or behavioral tracking tools such as Amplitude, Mixpanel, or similar platforms.
- Experience building or contributing to dashboards using BI tools such as Looker, Tableau, Power BI, or comparable solutions.
- Understanding of diagnostic analysis and the ability to interpret and communicate data-driven insights.
- Familiarity with A/B testing or A/A testing concepts and their role in measuring product improvements.
- Strong attention to detail and good judgment regarding data quality and accuracy.
- Clear communication skills and the ability to collaborate effectively with teammates and stakeholders.
- A proactive mindset with the ability to ask thoughtful questions, seek feedback, and continuously improve.
- Ability to work effectively in a remote environment and collaborate across teams.
Responsibilities
- Support product analytics initiatives by analyzing customer behavior, feature adoption, and product performance metrics.
- Build and maintain dashboards and reports that help Product and Technology teams monitor progress against key objectives.
- Work with behavioral and clickstream data to understand how users interact with products and identify opportunities for improvement.
- Support feature measurement initiatives, including analysis related to product launches and experimentation.
- Write and troubleshoot SQL queries to extract, analyze, and interpret data effectively.
- Collaborate with senior analysts and cross-functional teams to deliver accurate and actionable insights.
- Contribute to data quality efforts by identifying inconsistencies, validating results, and improving analytical processes.
- Communicate findings, progress, and recommendations clearly to technical and non-technical stakeholders.
- Support documentation, knowledge sharing, and analytics best practices across the team.
- Explore modern AI and business intelligence tools to improve analytical workflows and decision-making.
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