London, United Kingdom Hybrid Employment £76,500 to £95,000

Monzo is hiring a Senior Credit Analyst, Credit Cards

About the Role

As a Senior Credit Analyst, you'll lead the development and refinement of credit strategies for credit card products, ensuring a balanced approach to risk management, commercial performance, and customer experience. Your work will directly influence how lending decisions are made, from underwriting criteria to credit limit frameworks, using advanced analytics to guide sustainable growth.

What You'll Do

You'll analyse portfolio trends including arrears, utilisation, revenue, and loss performance to uncover insights that shape strategy. Using NPV and profitability models, you'll assess the long-term value of customer segments and test strategic levers. You'll develop segmentation approaches to pinpoint areas of risk concentration or revenue potential, and lead investigations into emerging portfolio behaviours.

Collaborating closely with Product and Engineering teams, you'll help design and evaluate new features and policy changes through data-driven experimentation. You'll translate complex findings into clear, actionable recommendations for senior stakeholders and ensure all strategies align with regulatory expectations and risk governance standards.

Requirements

  • Proven background in unsecured lending, with strong preference for credit card experience
  • Firm grasp of credit card financial dynamics, including APR, interchange, revolving patterns, and cost of funds
  • Track record in shaping credit strategies such as underwriting rules, limit policies, or pricing frameworks
  • Advanced analytical skills with fluency in SQL; experience with coding for data analysis is essential
  • Experience building or interpreting NPV models, profitability forecasts, and portfolio projections
  • Ability to communicate technical analysis clearly to non-technical audiences
  • Experience working across teams in fast-moving environments
  • Commitment to balancing risk, growth, and positive customer outcomes

Preferred Qualifications

  • Experience modelling rewards-based credit card products
  • Familiarity with Python and Looker
  • Background in UK-regulated lending operations
  • Exposure to IFRS9, stress testing, or capital modelling frameworks
  • Experience designing or evaluating strategy changes through controlled testing
  • Work with business lending portfolios

Technical Stack

Primary tools include SQL for data querying, Python for analytical modelling, and Looker for reporting and visualisation.

Work Mode

This is a hybrid role open to candidates across the UK. You can work remotely with flexibility to choose your schedule, including adapting around personal commitments. Occasional in-person meetings take place in London, but there is no expectation to work from an office regularly. The team values outcomes over presence, supporting a truly flexible approach to work.

Benefits

  • Flexible working hours designed to fit your lifestyle
  • Remote work across the UK with optional London meetups
  • No mandatory office attendance
  • Annual learning budget of £1,000 for courses, books, or conferences
  • Performance-based Incentive Awards
  • Relocation support for candidates moving to the UK
  • Visa sponsorship available
Required Skills
SQLPythonLookercredit card economicsunsecured lendingcredit strategyunderwritinglimit managementpricingNPV modelingprofitability analysisportfolio forecastingdata analysiscodinganalytical skills SQLPythonLookercredit card economicsunsecured lendingcredit strategyunderwritinglimit managementpricingNPV modelingprofitability analysisportfolio forecastingdata analysiscodinganalytical skills
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About company
Monzo
Monzo offers personal and business bank accounts, joint accounts, accounts for 16-17 year olds, free kids accounts, credit cards, savings, investments, and pension combination services in the UK. Known for hot coral cards, get-paid-early feature, financial education on social media, and award-winning customer service.
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Job Details
Department Data Team, Borrowing
Category data
Posted 9 hours ago