Lead Analyst, User Analytics & Insights
Leads performance marketing analytics to evaluate acquisition efficiency, customer quality, and long-term value. The role requires 7+ years of quantitative experience, advanced SQL, Python or R, marketing measurement expertise, experimentation skills, and strong stakeholder communication.
About the job
Responsibilities
- Serve as a senior analytical partner to Performance Marketing, Growth, Finance, and adjacent teams.
- Analyze CAC, ROAS, LTV, conversion, retention, downstream revenue, channel mix, media efficiency, audience composition, user quality, seasonality, and market dynamics.
- Support channel strategy, audience targeting, bidding, and budget allocation through rigorous analysis.
- Identify opportunities to improve marketing efficiency and quantify expected business impact.
- Develop analyses that explain performance changes and recommend actions.
- Partner on A/B tests, holdouts, lift studies, incrementality tests, and other measurement initiatives.
- Apply statistical and analytical methods to evaluate marketing effectiveness and communicate limitations, trade-offs, and confidence levels.
- Use SQL, Python, and visualization tools to conduct analyses across user-, campaign-, and event-level datasets.
- Build and maintain scalable reporting and analytical frameworks.
- Partner with Analytics Engineering and Data Science to improve data quality, measurement inputs, and reusable analytics infrastructure.
- Translate findings into persuasive business narratives and actionable recommendations.
- Present insights to senior stakeholders and influence decisions.
- Mentor junior analysts and contribute to analytics best practices.
Requirements
- 7+ years of experience in analytics, marketing analytics, growth analytics, data science, or a related quantitative field.
- Significant hands-on experience supporting performance marketing or paid media.
- Advanced SQL proficiency and experience with Python or R.
- Strong understanding of CAC, ROAS, LTV, conversion, and retention.
- Experience with Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA).
- Experience with experimentation, incrementality measurement, and A/B testing.
- Experience analyzing large-scale user, campaign, and conversion datasets.
- Exposure to customer segmentation, predictive modeling, propensity modeling, lifetime value analysis, or causal inference.
- Strong data visualization, analytical storytelling, and presentation skills.
- Ability to define analytical approaches for ambiguous business questions and translate findings into recommendations.
- Ability to influence cross-functional stakeholders and communicate complex concepts to non-technical audiences.
Nice to Have
- Experience with causal inference or advanced marketing measurement.
- Familiarity with Meta, Google, TikTok, Apple Search Ads, or programmatic advertising.
- Experience with mobile app or digital consumer acquisition.
- Familiarity with dbt, Git/GitHub, and modern analytics engineering workflows.
- Experience in consumer, marketplace, gaming, or e-commerce environments.
Compensation and Benefits
- Base salary: $148,723–$174,968.
- Equity for full-time employees.
- 401(k) match up to 4%.
- Medical, dental, and vision plans, including pet coverage.
- Education reimbursement up to $10,000 per year.
- Flexible paid time off and 9 paid holidays.
- Paid parental leave and flexible return-to-work scheduling.
- One-time $2,000 childcare-related incentive for employees welcoming new family members.
Skills
SQL, Python, R, Marketing Mix Modeling, Multi-Touch Attribution, A/B Testing, Causal Inference, Predictive Modeling, Propensity Modeling, Lifetime Value Analysis, dbt, Git, Tableau, Looker, Grafana
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