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Moneybox

Mobile fintech for savings and ISAs

Marketing Insight & Analytics Lead

Data AnalysisUpdated on Nov 10
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • At least 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 for data manipulation, data analysis, and modelling.
  • Direct experience with mobile attribution platforms, particularly AppsFlyer.
  • Familiarity with the privacy landscape across app platforms, including iOS SKAdNetwork, and the web, including cookie deprecation, and the resulting measurement challenges.
  • Experience working with advertising platform APIs, including Google Ads and Meta Ads, for data extraction and pipeline automation.
  • Familiarity with GCP data services and event analytics platforms such as Mixpanel or equivalent.
  • Demonstrable experience building data products and self-serve reporting assets used by non-technical stakeholders.
  • A track record of designing and analysing incrementality experiments or A/B tests in a marketing context.

Responsibilities

  • Assess and improve marketing tracking across paid, owned, and earned channels, identifying gaps in campaign tagging, event instrumentation, attribution, and measurement coverage.
  • Define standards for campaign taxonomy, tracking parameters, event definitions, and marketing measurement consistency across platforms.
  • Lead the definition of end-to-end web-to-app measurement requirements so customer journeys can be understood across acquisition, registration, onboarding, and downstream product engagement.
  • Use expertise in Google Analytics 4, AppsFlyer, and relevant advertising and product analytics tools to define how tracking should be implemented, validated, and maintained.
  • Establish measurement specifications, technical requirements, and acceptance criteria for engineering delivery.
  • Work with engineering teams to establish approaches for anonymous-to-known identity stitching, attribution identifiers, event mapping, and cross-platform journey continuity within applicable privacy and consent constraints.
  • Identify limitations in existing attribution data and recommend practical improvements.
  • Partner with stakeholders to translate business needs into a prioritised marketing analytics and data development roadmap.
  • Own marketing analytics requirements for Analytics Engineering, Data Engineering, and Product Engineering.
  • Define the data sources, integrations, event specifications, transformation requirements, and data products needed to improve marketing measurement.
  • Work with engineering teams to shape technical solutions, manage dependencies, and validate that delivered capabilities meet business and measurement requirements.
  • Establish data quality, reconciliation, and monitoring requirements for marketing data flows and tracking implementations.
  • Define and document sources of truth for key marketing KPIs, ensuring consistency across reporting surfaces.
  • Own the marketing reporting layer in Power BI or an equivalent tool, ensuring outputs are accurate, timely, and interpretable by non-technical audiences.
  • Use AI to automate routine reporting, draft performance narratives, and surface key trends or anomalies.
  • Serve as the primary data and analytics partner for Marketing, 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 and contribute to roadmap prioritisation.

Desired Qualifications

  • Experience with dbt Cloud or Core for transformation layer development.
  • Familiarity with Databricks or similar modern data lakehouse platforms.
  • Experience with Power BI or a similar data visualisation tool.
  • Experience in a regulated financial services or fintech environment.
  • Exposure to customer data platforms or CRM data integration, such as 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.

About the Company

Moneybox

Mobile fintech for savings and ISAs

Moneybox offers a mobile app that helps people save and invest by pairing automatic savings features with a range of investment and retirement accounts. Users link their bank cards and can have rounding-up of purchases feed into savings, then allocate funds into Cash ISAs, Lifetime ISAs, and Stocks and Shares ISAs, plus investment accounts and pension services. The app also charges subscription fees and management fees on its investment products, providing a simple, mobile-first way to grow wealth over time. What sets Moneybox apart is its focus on beginners and everyday users: a straightforward interface, automatic micro-savings, and an integrated suite of savings, investment, and pension options within one platform. The company aims to make saving and investing accessible to a broad audience—especially millennials and Gen Z—so they can build long-term wealth with minimal friction.

Company size
501-1,000
Company stage
Private
Total funding
$208.2M
Headquarters
London, United Kingdom
Founded
2015

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