Hybrid opportunity at
WiseSenior Analytics Manager - Credit Risk
Wise is seeking a Senior Analytics Manager - Credit Risk to join its Spend Squad in London on a hybrid work schedule. This full-time position plays…
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About This Role
Wise is seeking a Senior Analytics Manager - Credit Risk to join its Spend Squad in London on a hybrid work schedule. This full-time position plays a central role within the newly established Credit team, which focuses on delivering fair and transparent credit products to help customers manage their global finances. The person in this position will collaborate closely with a global group of engineers, product leads, data scientists, and…
Job Description
Wise is seeking a Senior Analytics Manager - Credit Risk to join its Spend Squad in London on a hybrid work schedule. This full-time position plays a central role within the newly established Credit team, which focuses on delivering fair and transparent credit products to help customers manage their global finances. The person in this position will collaborate closely with a global group of engineers, product leads, data scientists, and designers while taking on a hands-on approach to data and expanding a small analytics team as operations scale.
This opportunity is well-suited for an experienced data professional who brings a strong background in risk, finance, or economics. Responsibilities include validating credit risk models for SME customers, monitoring repayment metrics and expected losses, establishing data strategies, and leading a growing team of analysts. Wise offers a competitive compensation package ranging from GBP 105,000 to GBP 150,000 per year, alongside company restricted stock units and various office perks in London.
Responsibilities
- Collaborate with Data Science to stress-test and review credit risk modeling assumptions for SME customers, conducting sensitivity and scenario testing to keep decisions explainable and robust.
- Utilize market insights and public data on SME finance to support the validation of models and decisions.
- Build forward-looking projections regarding expected losses, delinquency transitions, write-offs, and repayment failures, while establishing feedback loops with risk and product decisions.
- Collaborate with regional teams to shape the strategy for market launches.
- Manage the credit analytics data strategy by creating the roadmap for dashboards, datasets, and tools necessary to scale decision-making while ensuring data quality and consistent documentation.
- Hire, mentor, and guide a high-performing team of analysts to elevate analytical quality and manage prioritization.
Requirements
- Have at least 6 years of experience in data analytics, with significant background in risk, finance, economics, fraud, portfolio management, or investment modeling and credit.
- Demonstrate a strong grasp of the credit ecosystem, including risk evaluation and the economics of different credit products.
- Possess robust technical abilities, including SQL experience handling large datasets and constructing data pipelines.
- Show a pragmatic, structured approach to zero-to-one initiatives, including setting up measurements and defining success without needing perfect information.
- Display strong communication and stakeholder management capabilities to influence across disciplines and protect focus.
Core Skills
Benefits
- Salary between GBP 105,000 and GBP 150,000 per year
- Company Restricted Stock Units
- Hybrid working arrangement in the London office
- Paid annual holiday, sick days, parental leave, and other leave opportunities
- Six weeks of paid sabbatical after completing four years at Wise
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location and remote work policy for this role?
The position is based in London with a hybrid working arrangement.
What is the salary range for the Senior Analytics Manager position?
The salary is between GBP 105,000 and GBP 150,000 per year, accompanied by company restricted stock units.
What experience is required to apply?
Applicants must have six or more years of experience in data analytics with substantial background in credit, risk, finance, economics, fraud, portfolio management, or investing modeling.
Sample Interview Questions
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