Growth Data Analyst – US Acquisition & Analytics

capitalontap; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Private Healthcare including dental

Worldwide travel insurance

Annual Learning and Wellbeing Budget

Pension scheme 7% match (Salary Sacr.

26 days holiday + holidays

Enhanced Parental Leave

Cycle to Work

Season Ticket Loan

Dog-friendly offices

Free drinks and snacks

Job summary

Capital on Tap is expanding its US Growth & Data Science capability to drive acquisition and portfolio expansion. You will own the data-driven US channel, build pipelines, and analyse campaigns to optimise performance across the customer lifecycle.

The role requires 4+ years in analytics/data engineering, strong SQL and experience with Looker/Tableau. Collaboration with data and engineering teams is essential in a fast-moving fintech environment.

Qualifications

• 4+ years' experience as Analytics/Data Engineer or Data Analyst in a fast-paced setting.
• Strong analytical/ quantitative skills and ability to frame business problems as analytical questions.
• Strong SQL skills and experience building complex datasets.

Responsibilities

• Own the delivery of a high-volume, data-driven US acquisition channel and contribute to its strategy.
• Build and maintain data pipelines (SQL, dbt) turning data into audience segments.
• Launch and optimise campaigns through analysis and testing.
• Find growth opportunities across the US customer lifecycle through analysis.
• Evaluate new data sources for marketing, underwriting, fraud and KYB.
• Collaborate with Data Engineering to productionise datasets and pipelines.

Skills

SQL

Analytical thinking

Python or R

Looker/Tableau

Campaign analytics

Education

Bachelor's degree in quantitative field

Tools

SQL

dbt

Looker

Tableau

Python

Job description

Capital on Tap is expanding its US Growth & Data Science capability to drive acquisition and portfolio expansion. You will own the data-driven US channel, build pipelines, and analyse campaigns to optimise performance across the customer lifecycle.

The role requires 4+ years in analytics/data engineering, strong SQL and experience with Looker/Tableau. Collaboration with data and engineering teams is essential in a fast-moving fintech environment.