What we are looking for: someone who understands paid marketing deeply (search, social, display, affiliates, etc.), can navigate the realities of attribution and tracking, and can translate multi-channel performance into decisions that improve CAC, ROAS, LTV, and payback. You should also be highly fluent with AI-driven analysis, confident inside each platforms native analytics, and able to use visualizations + AI to communicate insights and support data-driven decision making.
What youll be doing:
Own analytics for paid user acquisition across channels (paid search, paid social, display/programmatic, affiliates, partnerships, etc.) and across platforms (web, iOS, Android).
Build and maintain end-to-end performance visibility: click -> landing -> activation -> paywall -> purchase -> renewal/retention.
Develop and refine measurement approaches including:
attribution models (last-click, first-click, data-driven where available)
cross-channel cannibalization detection and analysis.
incrementality and lift thinking (geo tests/holdouts/controlled experiments where possible).
Use AI tools to accelerate analysis, explore hypotheses, detect patterns/anomalies, and generate high-quality insights.
Leverage each platforms native analytics tools (Google Ads, Meta, TikTok, DSPs, affiliate platforms, etc.) to understand what drives performance and to diagnose what is actually changing inside campaigns (creative, audiences, bidding, placements, pacing, attribution).
Monitor and optimize core performance KPIs tied to subscriptions: CAC, ROAS, CVR, LTV, payback period, churn/retention cohorts.
Own ongoing monitoring to proactively detect drops, tracking glitches, attribution breaks, spend/performance anomalies, and funnel issues, and drive resolution with relevant stakeholders.
Partner with UA managers and channel owners to identify opportunities, size impact, and prioritize actions (creative, targeting, bidding, landing pages, offers, paywall flows).
Deep dive into funnel drop-offs and cohort behavior by channel/campaign/audience/geo/device to explain whats driving performance.
What youll bring:
4+ years of experience in paid acquisition analytics/performance marketing analytics (hands-on, not only reporting), from a subscription-driven product company.
Strong understanding of the impact of paid traffic on subscription outcomes, and the ability to use visualizations to present insights and drive decisions.
Strong knowledge of paid channel mechanics and measurement realities (platform attribution limits, view-through vs click-through, cross-device, etc.).
Strong understanding of platform-native analytics and drivers of campaign performance (what good looks like and why).
Excellent SQL skills for extracting and analyzing large datasets (funnels, cohorts, segmentation, marketing spend joins).
Experience measuring subscription business outcomes: paywall funnels, conversion, retention, LTV, churn.
Familiarity with AppsFlayer and APPs user acquisition.
Strong analytical thinking with the ability to turn ambiguity into a structured approach and clear recommendations.
Excellent communication skills – able to explain attribution tradeoffs and results to technical and non-technical stakeholders.
Advantage / Nice to have:
Mixpanel (funnels, cohorts, retention, event governance).
Familiarity with fintech or financial products (advantage, not mandatory).
Experience with mobile measurement topics (e.g., MMPs, SKAN basics) if relevant.
Familiarity with experimentation frameworks (holdouts, geo tests, lift measurement).
Experience working with high-traffic consumer products and complex cross-channel journeys.
