Join a fast-growing, award-winning company with genuine ambition to improve people's financial lives.
Overview
£0
London Office
Organisation summary (max 150 words)
The Moneybox app is the simplest way to save and invest. Round up your purchases to the nearest pound and invest the spare change. At Moneybox, our mission is to give everyone the means to get more out of life by building wealth, whether they’re saving, investing, buying a home, or planning for retirement.
Role Summary
- Lead the design and build of marketing attribution framework
- Own incrementality testing and translate results into actionable media planning recommendations
- Develop standardised effectiveness metrics and reporting
- Act as the data lead for marketing technology stack
- Build and maintain marketing data products and reporting
- Serve as the primary data and analytics partner for the Marketing team
Role Requirements
- 5+ years in a marketing analytics, data science, or analytics engineering role
- Hands-on experience with multi-touch attribution methodologies
- Strong SQL skills
- Experience with mobile attribution platforms and advertising platform APIs
- Familiarity with GCP data services and event analytics platforms
About Moneybox
At Moneybox, our mission is to give everyone the means to get more out of life. We're guided by our belief that wealth isn't about the money, it's about the means to more - more freedom, opportunities, possibilities, and peace of mind. Moneybox is an award-winning wealth management platform, helping over one and a half million people build wealth throughout their lives, whether they’re saving and investing, buying their first home, or planning for retirement.
Job Brief
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
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
Who You Are
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
Experience & Skills
Essential
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