Data Science Manager, Credit Risk Analytics (Hybrid/Remote)

Cleo; España; Híbrido; EUR 111.000 - 170.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work

Equity

Pension plan

Private medical insurance

Mental health support

Descripción de la vacante

Cleo is seeking a Data Science Manager to lead measurement, monitoring, and optimisation of credit performance. You’ll own metrics, dashboards, and deep-dive analyses, guiding policy and product decisions within Risk & Payments.

This player-coach role blends hands-on analytics with people leadership, driving clear insights across arrears, yield, LTV, and portfolio health. You’ll guide a team of analysts, work with Credit Policy, Decision Science, Product, and Finance, and communicate findings to

Formación

• Strong analytical skills with fluency in SQL and Python.
• Interpret and communicate model performance metrics, feature importance, and confidence intervals.
• Background in collaborating with decision science or data science teams on feature engineering and model evaluation.
• Experience conducting large scale A/B experiments and interpreting results to drive product and business decisions.
• Fluent in credit portfolio metrics – e.g. arrears buckets, roll rates, loss rate, yield/marginal loss – and how they tie to unit economics and P&L.
• Experience building and maintaining performance monitoring systems and alerting frameworks.
• Hands-on experience working with predictive models (e.g. credit, fraud, marketing), including interpreting metrics like AUC/Gini, calibration, PSI/CSI, drift.
• Experience collaborating with commercial and finance teams on business metric forecasting.
• Track record of taking analyses all the way through to shipped changes and measurable impact.

Responsabilidades

• Own the design and maintenance of Cleo’s credit risk metric framework, including arrears, default, yield, LTV, and marginal loss rates.
• Build and maintain dashboards and alerts for early detection of arrears, roll-rate shifts, and decisioning anomalies.
• Ensure definitions, thresholds, and escalation processes are consistent, documented, and used company-wide.
• Partner with the Risk Modelling team to turn model health metrics into clear recommendations for policy or product changes.
• Detect and diagnose feature shift or concept drift, ensuring model inputs remain valid and predictive.
• Lead investigations into performance deviations, separating model-driven changes from macro or operational causes.
• Deliver driver analysis for changes in portfolio performance and quantify risk-adjusted impact of product features.
• Design and analyse multivariate experiments on underwriting, pricing, or repayment flows, translating results into risk strategies.
• Directly manage a team of Credit Data Scientists and Analysts, translate findings for leadership, and build cross-functional partnerships.

Conocimientos

SQL

Python

A/B testing

Credit risk metrics

Model evaluation

Leadership

Stakeholder management

Herramientas

SHAP

Descripción del empleo

Cleo is seeking a Data Science Manager to lead measurement, monitoring, and optimisation of credit performance. You’ll own metrics, dashboards, and deep-dive analyses, guiding policy and product decisions within Risk & Payments.

This player-coach role blends hands-on analytics with people leadership, driving clear insights across arrears, yield, LTV, and portfolio health. You’ll guide a team of analysts, work with Credit Policy, Decision Science, Product, and Finance, and communicate findings to