Data Analyst

I’m working with a growing financial technology client in London who are looking to hire an early-career Data Analyst into a maturing data function.

This would be a great role for a talented Data Analyst with aspirations of growing into a Data Science position over time. The immediate need is analytical and commercially focused, but you’ll be learning from a technically strong Data Scientist who can provide hands-on coaching and development.

This is not a deep data science or machine learning role from day one. It is a business-facing analyst position, working closely with finance, operations, marketing, and senior leadership to turn data into clear commercial insight.

The role will suit someone bright, curious, and early in their career who wants proper coaching, genuine exposure, and the chance to learn how a financial services business works from the inside.

You’ll report into a highly capable Data Scientist who is stepping into management and will provide hands-on technical guidance, with regular exposure to the Finance Director and CEO. The structure is flat, the data engineering team is already well established, and the environment is set up for someone to learn quickly without being left to figure everything out alone.

What you’ll be doing:

• Analysing commercial, finance, and operational data
• Spotting trends, opportunities, and areas for improvement
• Communicating insight clearly to non-technical stakeholders
• Working with established data processes and tooling
• Partnering closely with more senior people before running independently with ideas
• Building your commercial understanding of a fast-moving fintech environment, * 1st stage: Intro chat with senior finance and data stakeholders
• 2nd stage: Technical interview
• Final stage: In-office meeting with the wider leadership and data team

If you’re a Data Analyst who wants to build strong commercial foundations while developing towards Data Science over time, this could be a really strong fit.

• Strong SQL and some Python experience
• Exposure to modern data tooling such as dbt or Airflow
• Some experience with data visualisation and reporting
• Strong communication skills, especially with non-technical stakeholders
• High EQ, curiosity, and willingness to learn
• A collaborative mindset and the maturity to ask questions before building in isolation
• Fintech, financial services, or card issuing experience would be a bonus, but is not essential

The key here is attitude and commercial thinking. The client is not looking for someone who wants to disappear into technical work. They want someone who can understand a business problem, work with others, and explain findings in plain English.