Responsibilities

• Serve as a senior analytical partner to Performance Marketing, Growth, Finance, and adjacent business teams.
• Analyze performance across key metrics including CAC, ROAS, LTV, conversion, retention, and downstream revenue.
• Diagnose changes in acquisition performance, identifying drivers across channel mix, media efficiency, audience composition, user quality, seasonality, and broader market dynamics.
• Support decisions around channel strategy, audience targeting, bidding, and budget allocation through rigorous analysis.
• Proactively identify opportunities to improve marketing efficiency and quantify expected business impact.
• Develop deep-dive analyses that move beyond reporting to explain why performance is changing and what actions should be taken.
• Partner with Marketing on the design, execution, and analysis of A/B tests, holdouts, lift studies, and other incrementality tests.
• Apply appropriate statistical and analytical methods to evaluate marketing effectiveness when direct experimentation is not possible.
• Help improve measurement approaches across paid acquisition, balancing rigor, speed, and business needs.
• Evaluate performance across multiple measurement methodologies and clearly communicate limitations, trade-offs, and confidence levels.

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 proficiency in SQL and experience using Python or R for analysis.
• Strong understanding of performance marketing metrics including 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-level datasets.
• Exposure to customer segmentation, predictive modeling, propensity modeling, lifetime value analysis, or causal inference techniques.
• Strong data visualization and storytelling skills, with experience using tools such as Hex, Tableau, Looker, or Grafana.
• Proven ability to take ambiguous business questions, define an analytical approach, and translate findings into actionable recommendations.

Preferred

• Experience with causal inference or advanced marketing measurement techniques.
• Familiarity with major paid media ecosystems such as 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 working in a fast-paced consumer, marketplace, gaming, or e-commerce environment.