Easygenerator - Product Analyst
Requirements
• Exposure to experimentation and A/B testing. • Experience building AI agents or automated analytics workflows on Snowflake (e.g. Cortex AI, Snowflake notebooks). • Experience using Claude or similar AI assistants for analytics work, including MD-based skills/prompts and agent workflows. • Experience with product analytics platforms such as Mixpanel or Segment. • Familiarity with marketing or revenue analytics and attribution models. • Experience with dimensional modeling and modern data warehouse concepts (star/snowflake schemas). • Experience working with semi-structured data (JSON). • Ready to Join Us? • If you're curious about the "why" behind the numbers and want to help teams make smarter decisions with data, we'd love to hear from you. Apply today!
Responsibilities
• Run deep dive analyses and root cause investigations into product and business metrics. • Build and maintain dashboards and self-service reporting. • Scale analytics through AI-powered tools, including AI agents built on Snowflake and Claude-based workflows. • Partner with Product, Engineering, and Business stakeholders to define metrics and success criteria. • Track adoption and impact of product launches. • Validate or challenge product hypotheses with data to help shape the roadmap. • 3+ years as a Product Analyst, Data Analyst, or similar, ideally in B2B SaaS. • Advanced SQL skills, including complex joins, window functions, and query optimization on large datasets. • Strong hands-on experience with Snowflake for querying, modeling, and analytics workflows. • Proficiency in Python for data analysis and automation (Pandas, data wrangling, scripting). • Experience building dashboards and reports in Power BI, including data modeling and DAX. • Experience building analytics apps or internal tools using Streamlit. • Proven ability to turn ambiguous business questions into structured analysis and clear recommendations. • Experience running root cause analyses and communicating findings to stakeholders. • Solid understanding of product metrics, funnels, cohort analysis, and user behavior data. • Strong data storytelling skills and a data quality mindset. • Ownership mindset, strong problem-solving abilities, and attention to detail.
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