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KudaData Analyst - Credit
Kuda is hiring a Data Analyst for Credit to back analytics across the credit product lifecycle, which runs from product design and acquisition through portfolio management,…
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About This Role
Kuda is hiring a Data Analyst for Credit to back analytics across the credit product lifecycle, which runs from product design and acquisition through portfolio management, collections and profit and loss. The analyst works inside the Decision Science team and reports to the lead for credit risk analytics, turning data into decisions that influence lending and recovery activity. Duties include examining portfolio performance to surface trends, risks and openings, reviewing…
Job Description
Kuda is hiring a Data Analyst for Credit to back analytics across the credit product lifecycle, which runs from product design and acquisition through portfolio management, collections and profit and loss. The analyst works inside the Decision Science team and reports to the lead for credit risk analytics, turning data into decisions that influence lending and recovery activity.
Duties include examining portfolio performance to surface trends, risks and openings, reviewing credit policies and automated decision rules, and building profit and loss projections. The analyst assigns credit limits, assesses affordability, runs score cut-off studies to tune approval and risk settings, and refines collection approaches using segment data and results. Designing and running A/B experiments on lending and collections is part of the work, and so is presenting findings and suggestions to senior stakeholders.
The posting seeks a background in a numerate discipline such as mathematics, statistics or physics, and at least three years as a quantitative or data analyst in banking, fintech or online retail. Strong SQL, practical use of Python or R, and grounding in statistical tests used for A/B work are required. Building reports or dashboards from start to finish is expected. Familiarity with credit risk measures such as annualised loss, vintage analysis, roll rates, exposure at default and loss given default is a bonus. The role is full-time and on-site with a hybrid in-office schedule. No salary is stated.
Responsibilities
- Analyze portfolio results to surface trends, risks and openings
- Review credit policies and automated decision rules
- Build and keep current profit and loss forecasts
- Set credit limits and assess affordability
- Carry out score cut-off studies to tune approval and risk settings
- Improve collection approaches using customer segments and outcomes
- Set up and execute A/B experiments on lending and collection performance
- Present insights and suggestions to senior stakeholders
Requirements
- Background in a numerate subject such as mathematics, statistics or physics
- At least three years as a quantitative or data analyst in banking, fintech or online retail
- Strong SQL for pulling and reshaping data
- Hands-on Python or R skills
- Solid grasp of statistical tests used in A/B testing
- Familiarity with statistical software packages, open-source tools preferred
- End-to-end track record of producing reports and dashboards
- Ability to interpret results and present them to business audiences
Qualifications
- Knowledge of credit risk and portfolio metrics, including annualised loss, vintage analysis, roll rates, EAD and LGD (listed as a bonus)
Core Skills
Benefits
- Energetic, multinational colleagues
- Pension and career progression
- Annual leave plus holidays, and paid leave for family events, moving and study
- Group life and medical cover, plus a welfare scheme
- Wellness rewards, a wellness app and award-winning learning programs
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Who does the role report to?
The analyst reports to the head of credit risk analytics, within the Decision Science team.
What experience is required?
At least three years as a quantitative or data analyst in banking, fintech or online retail.
What technical skills are needed?
Strong SQL and hands-on Python or R, with knowledge of the statistical tests used in A/B testing.
What is the salary?
No salary is given.
Sample Interview Questions
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