Principal Product Analyst
New
J
JobgetherProduct Analytics
Based in United StatesFull-TimePrincipal
Salary$166,000 to $260,000 USD
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Job Details
- Experience
- 8+ years
- Required Skills
- SQLSnowflakeProduct Analyticsdbt
Requirements
- 8+ years of product analytics experience, preferably within consumer-facing, high-growth environments.
- Proven ability to independently identify important business questions, frame analytical problems, develop solutions, and communicate insights to the appropriate stakeholders.
- Demonstrated experience influencing product strategy through data-driven insights.
- Deep expertise in experiment design, causal inference, and power analysis.
- Daily experience using AI tools within analytical workflows, with understanding of where AI can accelerate analysis and where human judgment remains essential.
- Strong SQL skills and ability to work confidently with complex datasets.
- Experience with modern analytics and business intelligence tools such as Snowflake, dbt, Amplitude, Hex, or Mode.
- Excellent communication and storytelling skills, with the ability to explain statistical concepts to technical and non-technical audiences.
- Strong business judgment and strategic thinking.
- Self-directed, proactive approach to solving ambiguous problems.
Responsibilities
- Identify high-impact business and product questions, develop analytical frameworks to address them, and deliver clear recommendations that influence product and leadership decisions.
- Build a comprehensive understanding of customer behavior, including conversion, retention, engagement, and growth drivers, and translate those insights into strategic opportunities.
- Own experimentation strategy across assigned product areas, including experiment design, guardrails, interpretation, and analysis of patterns across multiple concurrent experiments.
- Evaluate AI-generated analyses and outputs for accuracy, relevance, and analytical rigor, while helping improve AI systems and workflows over time.
- Connect insights across product areas, experiments, and data sources to identify trends, quantify opportunities, and surface strategic recommendations that may not emerge from isolated analyses.
- Partner closely with Product, Design, Engineering, and executive leadership to ensure analytical insights are translated into meaningful product and business outcomes.
- Establish and promote high standards for analytical rigor, experimentation quality, metric validation, and effective use of AI across the broader analytics team.
- Continuously improve analytical workflows by identifying more efficient approaches to research, experimentation, validation, and insight generation.
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