Risk Data Analyst
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Requirements
• A hands-on, detail-oriented credit risk analyst who enjoys working directly in the data. • Highly numerate, structured, and intellectually rigorous. • Comfortable owning both the accuracy of numbers and the interpretation behind them. • Curious and proactive — you don’t just report metrics, you interrogate them with on a visceral feel for the data. • Able to translate complex analysis into clear, commercially relevant insights. • Comfortable working closely with senior stakeholders while maintaining analytical independence. • 1 - 2 years’ experience in credit risk, portfolio analytics, or a similar analytical role, or equivalent experience through studies. • Strong SQL skills and experience working directly with large datasets. • Experience building or maintaining dashboards (e.g. QuickSight, Tableau, Power BI, Looker). • Strong understanding of consumer credit performance metrics (arrears curves, roll rates, PD, loss rates, concentrations). • Experience across one or more lending products such as Unsecured Personal Loans (UPL), BNPL, Mortgages, or Auto finance is desirable. • Exposure to funding-related reporting, covenants, or performance triggers is a plus. • Comfortable working alongside data scientists and understanding model outputs, though not necessarily building models yourself.
Responsibilities
• Own the detailed production, validation, and enhancement of credit risk MI across products, channels, and geographies. • Write and optimise SQL queries to extract, reconcile, and analyse portfolio performance data. • Develop and maintain dashboards (e.g. QuickSight) covering credit performance, arrears, defaults, roll rates, concentrations, and risk triggers. • Analyse performance trends and identify emerging risks, concentrations, or behavioural shifts. • Support monitoring of internally defined risk limits and externally defined triggers arising from funding arrangements. • Provide deep-dive analysis to answer complex or ad hoc questions from the Head of Credit Risk & Reporting, CRO, Product teams, auditors and funders. • Generate actionable insights to inform product decisions, risk appetite calibration, and policy refinement. • Work closely with other data scientists to reconcile model outputs with realised performance and explain portfolio dynamics. • Contribute to audits, due diligence processes, and external reporting by ensuring data accuracy and analytical robustness.
Benefits
• Work at the heart of a fast-scaling credit business with market-leading performance. • Play a visible role in shaping risk appetite and product decisions. • Collaborate closely with the Head of Credit Risk & Reporting and the CRO. • Operate in a high-ownership environment where analytical rigor truly matters. • Everyone owns a piece of the company – equity. • Hybrid working with 3 days a week in the office. • 25 days’ holiday a year, plus 8 bank holidays. • 2 paid volunteering days per year. • One month paid sabbatical after 4 years. • Employee loan. • Free gym membership. • Team wellness budget to be active together – set up a yoga class, a tennis lesson or go bouldering.
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