Data Analyst – Growth Marketing; D2C
Listed on 2026-01-13
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IT/Tech
Data Analyst, Data Science Manager, Data Mining
Location: Greater London
We’re looking for a Data Analyst (Growth Marketing) to join our D2C Marketing team. The successful individual will accelerate the growth of our D2C business by delivering data-driven insights that enhance marketing performance, customer targeting and customer acquisition.
What you’ll be doing :The Data Analyst will play a key role in improving the efficiency and effectiveness of our acquisition marketing across paid channels, helping us to acquire higher-quality customers, improve LTV and optimise ROI.
Sitting within the Customer Acquisition team, this role will provide analytical expertise to performance marketers, while working closely with internal Data teams and an external analytics agency to advance our measurement capabilities, modelling and reporting infrastructure.
Working within a regulated financial services environment, this role ensures that data-driven recommendations align with compliance, risk, and governance standards, including consumer duty, and support and enable the business to deliver good outcomes for D2C customers.
Key Responsibilities:1. Performance Measurement & Optimisation
- Support performance analysis across digital and offline acquisition channels (e.g. paid search, paid social, programmatic, affiliates, partnerships).
- Contribute to optimisation strategies through data-led recommendations and test results.
- Track and evaluate key metrics such as cost-per-acquisition (CPA), conversion rate, ROI, and customer lifetime value (CLV).
- Provide clear, actionable insights to improve CPA, ROI, conversion rates, new funded account growth and overall acquisition efficiency.
- Support development of measurement and modelling frameworks including:
- Marketing Mix Modelling (MMM)
- Multi-Touch Attribution (MTA)
- Incrementality testing
- LTV and Propensity modelling
- Extract, transform, and validate data from multiple sources.
- Build and maintain automated dashboards and reports to monitor acquisition performance.
- Own weekly performance insights reporting and monthly deep dives to inform budget and optimisation decisions.
- Support data integrity by ensuring consistency, accuracy, and alignment with internal standards.
- Collaborate with data engineering and governance teams to maintain secure and compliant data environments.
- Conduct deep-dive analysis to uncover audience behaviours, segment performance, and channel synergies.
- Support the acquisition experimentation roadmap across channels, creative, messaging, landing pages and incentives.
- Partner with performance marketers and Product to define test hypotheses, success metrics, and measure impact to validate scale opportunities.
- Work closely with BI/Data Engineering to enhance data pipelines, tracking, event taxonomy and data structures that support accurate customer acquisition reporting.
- Work closely with marketing, finance, and digital teams to connect acquisition data with wider business outcomes.
- Translate technical findings into clear, actionable recommendations for non-technical audiences.
- Present insights through compelling visualisations and concise storytelling.
Competencies:
- 2-3 years’ experience as a Data Analyst or Marketing Analyst, ideally in financial services, fintech, or another regulated sector.
- Familiarity with Snowflake and Google Big Query and exposure to marketing mix modelling or attribution analysis.
- Strong SQL skills and experience working with large datasets.
- Experience using data visualisation tools (e.g., Power BI, Tableau, Looker).
- Hands-on experience with digital marketing data sources (Google Ads, Meta Ads, GA4, CRM systems and CDP platforms).
- Working knowledge of Python or R for data analysis and automation.
- Knowledge of paid digital media.
- Understanding of marketing analytics concepts (CPA, ROI, funnel analysis, attribution, CLV).
- Strong interest in AI and automation, with a desire to apply new technology to improve marketing performance and efficiency.
- Excellent communication skills, with the ability to explain complex data insights clearly.
- Excellent attention to detail.
- Project management and multi-tasking skills.
- Proactive self-learner with a continuous improvement…
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