Data Analyst, Product (Senior to Staff)
$180,000–$240,000 year
RemoteUnited States
Job Summary
Partner with product managers and engineering leads to frame questions, define analytical requirements, and deliver insights that shape roadmap and investment decisions. Build cohort, funnel, and user journey analyses explaining customer adoption, friction points, and retention drivers. Collaborate with Data Engineering to ensure data quality and consistency while defining north star and product health metrics. Own dashboard and self-service analytics development to provide trusted visibility into product performance. Communicate findings clearly to cross-functional stakeholders and leadership to influence strategic decisions. Manage ad-hoc and planned work while maintaining rigorous reporting standards. Based in San Francisco with a 5am start time to overlap with European partners.
Required Qualifications
- Based in: San Francisco
- The team comes into the SF office 2-3 times a week
- This role runs ~4 hours ahead of standard Pacific time
- 5am starts
- Early schedule works for you
- 4+ years of experience in Data Analytics, Business Intelligence, or a highly analytical role
- Hands-on exposure to product usage data, behavioral analytics, or event-level data at a SaaS company
- Advanced proficiency in SQL
- Advanced proficiency in Python
- Advanced proficiency in data modeling
- Ability to derive insights from complex datasets
- Ability to translate them into compelling visualizations and dashboards
- Familiarity with semantic layer BI tools (e.g., Omni, Looker)
- Familiarity with modern data stack tooling (e.g., dbt, Google BigQuery)
- Familiarity with event instrumentation platforms like CDPs (e.g., RudderStack, Segment)
- Fluency in cohort analysis
- Fluency in funnel and journey analysis
- Fluency in retention curves
- Ability to define metrics like north star, activation, and engagement
- Ability to work independently in ambiguous, fast-changing environments
- Ability to drive analytical work end-to-end from problem framing through implementation and iteration
- Excellent communication skills
- Ability to present complex findings to non-technical audiences
- Ability to turn analysis into recommendations stakeholders can act on
- Proven ability to navigate competing stakeholder priorities
- Proven ability to drive alignment across functions
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