Data Analyst, User Analytics & Insights

Responsibilities

Data Analysis & Business Partnership

• Partner with Product, Marketing, Growth, Engineering, and Business stakeholders to analyze user behavior, performance, engagement, conversion, and retention.
• Translate business questions into analytical plans using SQL, visualization tools, and statistical thinking.
• Conduct routine and ad hoc analyses to identify trends, diagnose metric movements, and surface opportunities.
• Communicate findings, implications, and recommended next steps to technical and non-technical stakeholders.
• Connect data insights to user experience, business outcomes, and team priorities.
• Document assumptions, definitions, methodologies, and findings.

Dashboarding & Reporting

• Build, maintain, and improve dashboards tracking business, product, marketing, app, and user behavior metrics.
• Create scalable self-service reporting and reduce one-off data requests.
• Ensure dashboards are accurate, documented, and easy for cross-functional partners to use.
• Monitor core KPIs and investigate trends, performance changes, and data quality issues.
• Partner with Analytics Engineering and Data Engineering to improve data definitions, reporting logic, and source-of-truth assets.

Experimentation & Measurement

• Support experiment setup and design, including hypotheses, metric selection, audience definition, and test-readiness checks.
• Conduct MDE calculations, power analysis, and sample-size estimates.
• Analyze A/B test results, including topline impact, segment-level performance, statistical significance, and follow-up questions.
• Partner with Product, Marketing, and Data Science teams to ensure consistent experiment measurement and interpretation.
• Communicate experiment results to support launch, iteration, or discontinuation decisions.

User Segmentation

• Create and maintain user segments for analysis, experimentation, lifecycle programs, product experiences, and reporting.
• Analyze cohorts based on behavioral, lifecycle, engagement, acquisition, and product-usage signals.
• Analyze opportunities to improve engagement, conversion, retention, and monetization across user groups.
• Support audience sizing, segment-performance tracking, and initiative readouts.
• For marketing-focused work, support campaign and lifecycle audience creation.
• For apps-focused work, support segmentation related to app usage, feature adoption, engagement, and product funnels.

Requirements

• 2+ years of experience in analytics, data analysis, product analytics, marketing analytics, business analytics, or a related field.
• Strong proficiency in SQL for data manipulation, analysis, validation, and reporting.
• Experience building dashboards and visualizations with tools such as Hex, Tableau, Looker, Grafana, Mode, or similar platforms.
• Working knowledge of A/B testing, including hypothesis creation, metric selection, sample sizing, segmentation, and result interpretation.
• Experience creating user segments, cohorts, or audience groups for analysis, experimentation, reporting, or targeting.
• Ability to analyze funnels, retention, engagement, conversion, campaign performance, app behavior, and other user or business metrics.
• Strong attention to detail and ability to identify data quality issues.
• Strong communication skills with technical and non-technical audiences.
• Ability to independently manage routine analytical requests and clearly escalate ambiguity, blockers, or trade-offs.
• Comfort working in a fast-paced environment with evolving priorities and imperfect data.

Nice-to-Haves

• Experience with dbt or analytics engineering workflows.
• Experience using Git or GitHub for version control, collaboration, or code review.
• Experience with Python for data analysis, automation, visualization, or statistical analysis.
• Familiarity with martech, lifecycle marketing, campaign platforms, CDPs, attribution, or audience activation tools.
• Familiarity with app analytics, event-based tracking, product instrumentation, feature adoption analysis, or app engagement metrics.
• Experience partnering with Product, Marketing, Growth, or Engineering teams.
• Comfort using Google Sheets for collaboration and lightweight analysis.

Compensation & Benefits

• Base salary range: $92,331-$108,625.
• Competitive compensation package including base salary, equity, and benefits.