Senior Product Data Analyst- Consumer Growth

Role overview

SumUp is looking for a Senior Product Data Analyst (Consumer Growth) to join the Consumer tribe. You’ll be the analytical partner for SumUp Consumer—translating customer behavior into insights that shape product strategy and drive measurable business outcomes across acquisition, activation, engagement, retention, churn, and reactivation.

Responsibilities

• Analyze customer behavior and product performance across the consumer lifecycle (acquisition → activation → engagement → retention → churn → reactivation).
• Improve conversion and sustainable growth using funnel analysis, cohort analysis, segmentation, and behavioral analytics.
• Partner with Product Managers, Designers, Engineers, and the Analytics Engineering team to ensure decisions are grounded in robust analysis and commercial context.
• Evaluate performance by customer segments, markets, channels, and product journeys; surface growth opportunities and trade-offs.
• Support decisions impacting key outcomes and metrics such as activation, conversion, repeat usage, retention, churn, CLV, and revenue-related metrics.
• Conduct exploratory analysis and turn complex data into clear, commercially relevant recommendations.
• Define, monitor, and communicate core SumUp Consumer KPIs (acquisition, activation, engagement, conversion, retention, churn, customer value).
• Design, execute, and analyze A/B tests and product experiments; assess customer impact and commercial impact.
• Build and maintain dashboards/reporting to proactively surface trends, anomalies, risks, and opportunities.
• Ensure KPI definitions, business logic, and product instrumentation are accurate, scalable, and trusted with Analytics Engineering.
• Apply a curious, practical approach to AI/ML, including LLM-assisted analysis, to accelerate insight generation and product measurement.

Requirements

• Strong SQL skills; able to query, analyze, and validate data in a cloud data warehouse such as Snowflake or BigQuery.
• Hands-on product analytics experience including funnel analysis, cohort analysis, segmentation, and behavioral analysis.
• Understanding of the commercial drivers of a digital product (acquisition, conversion/activation, retention/churn, and growth metrics).

Nice to have

• Familiarity with AI/ML techniques for analytics (e.g., LLM-assisted analysis).