moneyboxapp - Marketing Insight & Analytics Lead - Mat Cover (9 Month FTC)
Requirements
• A senior individual contributor who is comfortable building technical solutions as you are communicating them to non technical stakeholders • Deeply curious about marketing effectiveness: you have opinions about the limits of last-click attribution and the conditions under which MMM is and isn't trustworthy • A clear communicator who can make complex measurement concepts accessible to marketing and commercial stakeholders without dumbing them down • Excited about fintech and the particular measurement challenges that come with a regulated, app-first, long-consideration financial product • Comfortable with ambiguity and able to operate with autonomy in a fast-paced environment where the brief sometimes evolves mid-sprint • 5+ years in a marketing analytics, data science, or analytics engineering role with a strong focus on marketing measurement • Hands-on experience with multi-touch attribution methodologies and media mix modelling • Strong SQL skills; experience using it for data manipulation, data analysis, and modelling • Direct experience with mobile attribution platforms, particularly AppsFlyer • Familiarity with the privacy landscape across both app (e.g. iOS SKAdNetwork) and web (e.g. cookie deprecation), and how to navigate the resulting measurement challenges • Experience working with advertising platform APIs (Google Ads, Meta Ads) for data extraction and pipeline automation • Familiarity with GCP data services and event analytics platforms (Mixpanel or equivalent) • Demonstrable experience building data products and self-serve reporting assets used by non-technical stakeholders • Track record of designing and analysing incrementality experiments or A/B tests in a marketing context • Experience with dbt (Cloud or Core) for transformation layer development • Familiarity with Databricks or similar modern data lakehouse platforms • Experience with Power BI (or similar data visualisation tool) • Experience in a regulated financial services or fintech environment • Exposure to customer data platforms (CDPs) or CRM data integration (e.g. Braze) • Experience working within or alongside analytics engineering teams and contributing to shared data models • Understanding of CI/CD practices for data pipelines • Experience with Python for data manipulation, modelling, and pipeline work • ## Whats In It For You • Join a fast-growing, award-winning company with genuine ambition to improve people's financial lives • Work in a team that takes data quality and analytical rigour seriously, with a modern stack and strong engineering culture • Dedicated, focused remit – you'll be the subject matter expert in your domain, with real ownership and visibility • Hybrid working: 2 days from our London office, 3 from home
Responsibilities
• Marketing Measurement & Attribution • Lead the design and build of Moneybox's marketing attribution framework • Own incrementality testing: design experiments, define holdout groups, and translate results into actionable media planning recommendations • Develop standardised effectiveness metrics and reporting that span paid, owned, and earned channels • MarTech Data & Infrastructure • Act as the data lead for Moneybox's marketing technology stack, assessing the current state of play and designing the roadmap to make improvements to the data underpinning • Partner closely with Analytics Engineering and Data Engineering teams to ensure martech data flows (AppsFlyer, Google Ads API, Meta Ads API, GCP, Mixpanel) are well-modelled, documented, and trusted • Contribute to the design and governance of marketing data models within the broader data platform (Databricks), including gold/silver/bronze layer definitions relevant to marketing use cases • Identify and close gaps in marketing data coverage; define requirements for new integrations and own their delivery where appropriate • Data Products & Reporting • Build and maintain marketing data products – from campaign performance dashboards to customer acquisition cost models – that are used regularly by marketing leads and senior stakeholders • Define and document sources of truth for key marketing KPIs, ensuring consistency across reporting surfaces • Own the marketing reporting layer in Power BI (or equivalent), ensuring outputs are accurate, timely, and interpretable by non-technical audiences • Leverage AI to automate routine reporting, draft performance narratives, and surface key trends or anomalies • Stakeholder Partnership • Serve as the primary data and analytics partner for the Marketing team, translating commercial questions into analytical briefs and technical requirements • Support media planning cycles with data-driven audience segmentation, channel mix analysis, and budget allocation modelling • Represent the Data & Insight team in cross-functional marketing planning forums, contributing to roadmap prioritisation
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