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Remote role, mid-level seniority, and broad generalist analytics skills increase applicant competition significantly.
Skills are transferable across SaaS product teams, though AI/token economics and ClickHouse experience create moderate domain specificity.
Explicit 6+ years requirement plus mandatory SQL, ClickHouse/Snowflake, Superset and product analytics experience raises strictness.
Own and run the recurring business review for HighLevel's AI product portfolio, including metric definition, performance reporting, and variance analysis against operating plans.
Build and maintain SQL-based reports, dashboards, and data pipelines in Superset, ClickHouse, and Snowflake to track retention, adoption, unit economics, and product quality metrics.
Collaborate closely with product leadership and managers to inform AI roadmap decisions, formulate data-driven insights, and verify accuracy of all reported figures.
At least six years of experience in product or business analytics working directly with product teams.
Proficient in SQL including multi-CTE, window functions, cohort analysis, and querying semi-structured JSON in Snowflake; experience with cloud data warehouses like ClickHouse and Snowflake.
Experience building and maintaining dashboards and datasets in Superset or Tableau; familiar with product analytics tools such as Pendo, Amplitude, or Mixpanel.
Work Experience Required: Minimum 6 years in relevant analytics roles.
Experienced in managing recurring metrics packs or business reviews relied upon by leadership and product teams, demonstrating ownership and data accuracy stewardship.
Strong command of SaaS product analytics including metrics like MRR, ARR, churn, retention, ARPU plus statistical grounding to evaluate experiments and cohort analysis.
Familiarity with AI or LLM product analytics, token consumption and cost metrics, or usage-based pricing models is a plus but not mandatory.