Performance Marketing Data Analyst

Responsibilities

• Analyze paid-media performance across campaigns, audiences, placements, and individual creatives.
• Translate results into specific budget recommendations: what to scale, hold, reduce, refresh, or stop.
• Evaluate creative performance by format, hook, message, offer, visual style, spokesperson, length, and other meaningful attributes.
• Build and maintain a consistent creative taxonomy so results can be compared across concepts and over time.
• Develop dashboards and decision-ready reporting for metrics such as spend, CAC/CPA, ROAS, conversion rate, CTR, CPM, frequency, and downstream customer value where data permits.
• Identify creative fatigue, audience saturation, diminishing returns, and emerging winners early enough to act on them.
• Design a structured testing roadmap, including clear hypotheses, test design, sample-size considerations, success criteria, and post-test recommendations.
• Distinguish meaningful performance changes from noise and avoid decisions based on incomplete or misleading data.
• Reconcile platform-reported results with first-party analytics and business outcomes; identify tracking or attribution gaps.
• Partner with creative and agency teams to turn findings into clear briefs for the next round of concepts and variants.

Requirements

• 3+ years in performance analytics, growth analytics, marketing science, paid-media analytics, or a closely related quantitative role.
• A proven record of using data to improve paid-advertising efficiency or growth—not only producing reports.
• Strong SQL and advanced spreadsheet skills.
• Experience analyzing paid-social or paid-search data, ideally including Meta Ads and at least one additional major platform.
• Working knowledge of CAC/CPA, ROAS, conversion funnels, attribution, incrementality, cohort analysis, and marginal returns.
• Experience designing and interpreting A/B tests or other structured experiments.
• Ability to build clear dashboards and communicate a recommendation, not just a collection of metrics.
• Strong judgment when data is incomplete, delayed, or affected by platform attribution limitations.
• Ability to collaborate effectively with creative professionals, media buyers, agencies, and company leadership.

Preferred

• Experience analyzing creative at the asset or attribute level, including creative fatigue and performance by hook, angle, format, or message.
• Familiarity with tools such as Meta Ads Manager, Google Ads, GA4, Looker Studio, Power BI, Tableau, or similar platforms.
• Experience with Python or R for deeper analysis, automation, or forecasting.
• Experience joining ad-platform data with CRM, revenue, or customer-lifetime-value data.
• Experience in a high-growth, direct-response, ecommerce, lead-generation, subscription, or multi-brand environment.
• Familiarity with marketing mix modeling, lift testing, or causal inference.