Product Analytics Manager

Versant•Los Angeles, CA

6h•$110,000 - $130,000•Hybrid

About The Position

We're looking for a strategic and data-driven Product Analytics Manager to advance our streaming and ticketing platforms, driving audience growth and revenue. This role will lead analytics initiatives that enhance content discovery, improve conversion, and optimize the end-to-end streaming and ticketing experience. You'll partner closely with Product, Content, Marketing, and Engineering teams to translate data into insights that inform product decisions, improve customer experiences, and accelerate growth & monetization.

Requirements

5+ years of experience in product analytics, preferably within media, entertainment, streaming or digital commerce
Strong hands-on experience with Adobe Analytics (required)
Advanced proficiency in SQL for large-scale data analysis (required)
Experience with cloud data platforms (e.g. Databricks, Snowflake, Redshift)
Experience analyzing user engagement, content performance, and conversion funnels within subscription or transactional business models
Proven experience with A/B testing and experimentation frameworks
Experience with data visualization tools (e.g., Tableau, Looker)
Strong storytelling skills with the ability to communicate insights to both technical and non-technical audiences

Responsibilities

Define and track product KPIs across the user lifecycle, including feature adoption, conversion and engagement
Analyze cross-platform user behavior (web, mobile, CTV) to identify opportunities to improve discovery and conversion
Partner with Product to evaluate feature performance and prioritize enhancements
Identify friction points in user journeys and recommend solutions to improve conversion and revenue
Collaborate cross-functionally to support and execute conversion-focused initiatives
Design and analyze A/B tests to optimize product experiences and improve purchase completion
Develop dashboards and reporting to monitor product performance and funnel metrics
Leverage Adobe Analytics and large-scale behavioral datasets (via SQL) to generate actionable insights on user engagement, content performance, and conversion
Partner with Data Engineering and Data Implementation teams to improve tracking, data quality, and analytics reliability
Present insights and recommendations to inform product strategy