A sophisticated fintech operation in Estonia is seeking a Fintech Credit Risk Modelling Lead to develop and enhance analytical models used to assess credit exposure, portfolio performance, customer risk, and lending decisions.

This is a high-impact analytical position for a professional who can combine quantitative modelling with practical financial decision-making. You will work closely with risk, product, data, and engineering teams to transform complex financial data into robust risk frameworks.

Key Responsibilities

• Lead the development and continuous improvement of credit-risk models across lending products.
• Design analytical frameworks for credit assessment, portfolio segmentation, and risk forecasting.
• Evaluate model performance, stability, predictive power, and potential sources of bias.
• Develop statistical approaches for probability of default, loss estimation, and portfolio risk.
• Work with data engineers to establish reliable datasets for modelling and monitoring.
• Translate complex modelling outputs into clear recommendations for senior stakeholders.
• Develop monitoring frameworks for model performance and portfolio deterioration.
• Support stress testing, scenario analysis, and risk forecasting initiatives.
• Collaborate with product teams to incorporate risk intelligence into lending journeys.
• Contribute to model documentation, governance, validation, and review processes.
• Mentor quantitative analysts and develop internal modelling standards.

Candidate Profile

• 7+ years of experience in credit risk, quantitative finance, data science, banking, or fintech.
• Strong knowledge of statistical modelling, probability theory, and predictive analytics.
• Practical experience with credit-risk methodologies and financial datasets.
• Advanced Python, R, SQL, or equivalent analytical programming experience.
• Strong understanding of model validation and performance monitoring.
• Excellent communication skills with the ability to explain quantitative findings to non-technical stakeholders.

Analytical Environment

The role involves predictive modelling, statistical analysis, portfolio analytics, scenario modelling, automated risk monitoring, financial datasets, and modern cloud-based analytical infrastructure.

Why This Opportunity

You will influence how financial risk is measured and managed within a technology-driven lending environment, combining quantitative depth with direct business impact.

Ideal Candidate: A commercially aware quantitative professional who can build sophisticated models while understanding how those models translate into responsible financial decisions.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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