We're looking for a senior Marketing Insight & Analytics Lead to join the Data & Insight team on a fixed-term basis. This role is dedicated to supporting our Marketing function, acting as the analytical and technical centre of gravity for everything from campaign measurement to martech data infrastructure.
You'll work at the intersection of data engineering, analytics engineering, and marketing strategy. You'll refresh the measurement frameworks that tell us whether our marketing is working, and build the data products that make those answers repeatable and trusted.
What You'll Do
- 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
- Own the analytical view of Moneybox’s marketing data, assessing the current state of play and defining the roadmap for improving the data underpinning our measurement
- Partner closely with Analytics Engineering and Data Engineering teams to ensure martech data flows (AppsFlyer, Google Analytics, Google Ads API, Meta Ads API, GCP, Mixpanel) are well-modelled, documented, and trusted
- Define the requirements for marketing data models within our broader data platform (Databricks) and work with Analytics Engineering on their design and governance
- Identify gaps in marketing data coverage and define the requirements for closing them, partnering with Analytics Engineering on delivery
- 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
- 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
Stakeholder Partnership
Who You Are
- A senior individual contributor who is as 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
Experience & Skills
- 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 Desirable
- 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
- Competitive FTC compensation package
Skills Required
- 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, analysis, and modelling
- Direct experience with mobile attribution platforms, particularly AppsFlyer
- Familiarity with privacy-related measurement challenges (e.g., iOS SKAdNetwork, cookie deprecation)
- 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 (e.g., Mixpanel)
- Demonstrable experience building data products and self-serve reporting assets for 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 data lakehouse platforms
- Experience with Power BI or similar data visualisation tools
- Experience in a regulated financial services or fintech environment
- Exposure to customer data platforms or CRM integrations (e.g., Braze)
- Experience working with 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
What We Do
At Moneybox, we help you turn your money into something greater. Millions of us want to achieve more with our money. But whether we’re looking to save for a rainy day, grow our money, buy a home, or even build a retirement fund, we leave it at the bottom of our to-do lists because we're not sure how to get started. This isn’t surprising. We aren’t taught about financial planning at school, the wealth industry was built to serve a minority, and it often feels like banks don’t care about helping us achieve outcomes. To top it off, the financial services industry is fragmented and confusing. This means that our money often isn’t working hard enough and our goals are much harder to achieve. So, we made a solution. We've brought saving, investing, home-buying, and retirement services together into one simple app. So people can reach their goals and build wealth with confidence, whatever their starting point. We want to help people build wealth, but our mission goes beyond that. We believe that building wealth isn’t simply about accumulating more money. It’s about going after the life you want and enjoying it to the fullest, today and tomorrow. This is what it means to turn your money into something greater.
