Senior Analyst (Fraud & Financial Crime)

The role

You will analyse data and build controls to prevent fraud and financial crime, starting with card transactions, card tokens and account takeover. You will own the analysis, implementation and ongoing performance of the rules and models that protect customers.

What you will do

• Analyse, implement, test and optimise rules and other controls that prevent and detect fraud and financial crime.
• Use data to identify suspicious patterns and recommend ways to respond to emerging risks.
• Monitor detection, losses, false positives and alert volumes to measure control performance.
• Develop hypotheses and test new approaches, balancing detection with the impact on genuine customers and Operations.
• Work with Data Science, Product and Engineering on new data, models, AI and automation for detection.
• Help implement and monitor model-led controls, and test and migrate controls as platforms evolve.
• Work with the squad to identify and prioritise opportunities.

Required qualifications

• Strong analytical experience and advanced SQL skills, including working with large, complex datasets.
• Experience using Python for analysis, or the ability and willingness to develop those skills.
• A track record of owning complex analytical problems from question through to recommendation or implemented change.
• The ability to turn an open-ended problem into a clear analytical approach.
• Experience using data to assess performance, identify opportunities and make decisions.
• An understanding of basic machine learning concepts and performance metrics, such as precision and recall, or exposure to using them to assess controls.
• Sound judgement and the ability to balance analytical rigour with timely decisions.
• The ability to tell a clear story with data and influence technical and non-technical stakeholders.
• A collaborative approach and confidence working across teams and levels of seniority.
• Curiosity about new tools and an interest in using AI and automation.

Nice to have

• Experience in fraud, financial crime, risk analytics or another controls-focused environment.
• Experience analysing card transactions, payments or customer behaviour.
• Stronger experience working with machine learning models, including evaluating, implementing or monitoring their performance.
• Experience using AI tools such as Claude to support analysis, coding or automation.
• Exposure to decisioning systems, rule-based controls or experimentation.
• Experience with data visualisation tools such as Tableau.
• Experience in financial services, fintech or another fast-moving, product-led environment.

Benefits

• Flexible ways of working, with a hybrid role.
• Option to work from abroad for up to 120 days a year, subject to right to work.
• Support for work-life balance, and everything needed to thrive in work and home life from day one.

Before you apply

• You do not need prior fraud or financial crime experience.
• Working from abroad depends on having the right to work in the country of choice.
• Interview stages: recruiter screening (30 minutes), SQL technical assessment (1 hour), analytics case study (1 hour), final interview in the office (1 hour).
• Behavioural and competency-based interviews: AI use is not permitted. Technical stages may or may not allow AI; the Talent Partner will say what is expected at each stage.

About the company

Zopa started in 2005 as a peer-to-peer lending company and launched Zopa Bank in 2020. The posting says it has been named in the top three UK's Most Loved Workplaces.