Summary
✨ AI‑Generated
A Senior Data Analyst is sought to own data insights at both strategic and operational levels. You will analyze and model customer behavior, translate findings into commercial improvements, establish KPI structures, maintain consistent data definitions and data quality, and deliver dashboards and deep-dive analyses to support critical business decisions.
Highlights
Strategic senior analytics role with direct influence on growth, pricing, retention, conversion, revenue, and international expansion. Offers close collaboration with leadership and multiple business functions while combining strategic insight with hands-on data work.
Description
As a Senior Data Analyst, you are both strategically and operationally responsible for our data insights.
You will operate at the heart of our organization, working closely with the MT, Marketing, Finance, and Development teams.
Marketing budgets are growing, experiments are running in rapid succession, and critical choices regarding growth, pricing, and international expansion rely heavily on data.
This means you will tackle complex problems with a direct impact on the company's trajectory.You will analyze and model customer behavior to understand exactly where our growth comes from.
You will translate your insights into concrete improvements regarding retention, conversion, and revenue, driving direct commercial impact.At the same time, you will build the foundation that makes this possible.
You will develop a clear KPI structure, ensure consistent data definitions, and guard the quality of our data sources.
Through dashboards and deep-dives, you ensure that teams and management always have reliable information to guide their decisions.
You present insights to management, help teams evaluate hypotheses and experiments, and actively advise on the strategic questions our company should be asking next.You determine the course in the field by means of:models and analyses around customer behavior to implement changes with large commercial impact, think of marketing efficiency (CAC/CLV), cohort analyses, churn and retention, funnel analyses, and experimentation (A/B testing).a clear KPI structure, consistent data definitions, and high data quality.dashboards and insights that help teams make better-substantiated decisions.Our tech stackWe work with a pragmatic data stack and are open to improvement.
You think along about how we can further professionalize our tooling and data processes.
We encourage the use of AI when this helps to set up analyses, data processing, and reporting faster and more efficiently.
At this moment, we work with among others:Python for analyses and modelingTableau and Looker Studio for dashboarding and data visualizationSQL for data processing
