ironquill.tech/board

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Senior Marketing Data Analyst - Marketing Mix Modelling

N26·EU·Berlin·senior
data science
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About the opportunity As a Senior Marketing Data Analyst - Marketing Mix Modelling focusing on our Acquisition segment, you will enable our Marketing team to make data-driven decisions. You will monitor, measure and anayze the effectiveness of your marketing teams’ initiatives, as well as help drive the strategy of your stakeholder teams. You are here to establish a data-mindset and thereby to foster a culture of continuous learning and improvement. You will work in a cross functional setup, working closely with other analysts, engineers, scientists and marketing managers. In this role, you will: Act as the Analytics focal point on Marketing Mix Model (in collaboration with Data Science & Analytics Engineering); own the Acquisition Marketing Test & Learn the work stream end-to-end, from experiments design to analysis and share-out. Lead Acquisition Measurement: own the Acquisition Marketing Measurement domain roadmap and prioritisation with stakeholders from both Business and Technical backgrounds. Act as a Partner to Marketing Stakeholders: be the internal go-to-person for the acquisition Marketing teams (incl. Paid Media, Marketing Strategy, Friend Referral, Product Marketing) for measurement strategy and data related questions. Collaborate with Senior Leadership: advising on Measurement techniques, evaluating and presenting results or complexity analysis on a strategic level, helping to steer business decisions that drive overall company success. Build scalable, reliable, and self-serve resources: Enrich analytics foundations through Measurement Frameworks, scalable Data Modeling lineage, and design (and maintain) Analytics dashboards that allow Marketing Teams to interact with data to monitor channel and campaigns performance and extract the right insights themselves. Enrich knowledge base and drive data literacy: proactively contribute to the company knowledge base (e.g documenting insights, researches, data models, and data products), enable and share knowledg

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