Product Analyst

Overview

Turn product usage data into clear insights that shape what gets built next and how customers get value from the product.

What you'll do

• 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.

What you'll need

• 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.

Nice to have

• 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).