—
Experteer Overview As a Senior Credit Risk Data Scientist at Wayflyer, you will lead the Quantitative Risk Team’s modeling and risk outputs. You’ll bridge theory and business impact, scaling global funding operations to drive revenue growth. You’ll treat ML as production software, owning end-to-end credit risk model lifecycles and ensuring fast, robust outputs. You’ll translate analytics into strategic decisions and uphold scientific integrity while mentoring teammates. Pay / Benefits • Lead end-to-end production-grade ML lifecycle for credit risk models • Design and implement advanced risk modelling frameworks (e.g., decisioning, pricing, fraud) • Develop data-driven credit policies and lending strategies to expand addressable market • Ensure statistical rigor and guard against data leakage and bias • Translate model performance into business trade-offs for leadership (revenue vs. loss) • Set coding standards, perform code reviews, and mentor junior team members Tasks • 4+ years of Data Science/ML experience with production-grade systems • Advanced knowledge of predictive modeling and credit risk concepts (IV, ROC AUC, SHAP) • Proficiency in Python and SQL; experience with modern monorepos and tools (Snowflake, dbt, ZenML, Dagster, Weights & Biases) • Ability to leverage AI/LLMs to improve outputs • Deep understanding of credit risk metrics (PD, EAD, LGD, EL) and risk-growth trade-offs • Strong communication skills to convey risk strategy to non-technical stakeholders Key requirements • 25 days of paid annual leave • private healthcare • life insurance • critical illness cover • pension plan • equity scheme
| Skill | Source | Confidence |
|---|---|---|
| Python | llm_hard |
100%
|
| SQL | llm_hard |
100%
|
| Supervised Learning | llm_hard |
100%
|
| Large Language Models (LLMs) | llm_hard |
80%
|
| Model Deployment | llm_hard |
80%
|
| Model Performance Optimization | llm_hard |
80%
|
| Skill | Source | Confidence |
|---|---|---|
| Mentoring | llm_soft |
100%
|
| Decision-Making | llm_soft |
100%
|
| Stakeholder Communication | llm_soft |
100%
|
| Leadership | llm_soft |
100%
|
| Strategic Thinking | llm_soft |
100%
|
| Collaboration | llm_soft |
80%
|
| Written Communication | llm_soft |
80%
|
| Verbal Communication | llm_soft |
80%
|
| Query | Country | Status | Response ms | Created |
|---|---|---|---|---|
| Senior Credit Risk Data Scientist | extracted | 4734 | 2026-03-22 02:14 | |
| Senior Credit Risk Data Scientist | classified | 445 | 2026-03-21 20:57 | |
| junior data scientist in London | gb | processed | 15834 | 2026-03-21 16:54 |
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"job_description": "Experteer Overview\nAs a Senior Credit Risk Data Scientist at Wayflyer, you will lead the Quantitative Risk Team’s modeling and risk outputs. You’ll bridge theory and business impact, scaling global funding operations to drive revenue growth. You’ll treat ML as production software, owning end-to-end credit risk model lifecycles and ensuring fast, robust outputs. You’ll translate analytics into strategic decisions and uphold scientific integrity while mentoring teammates.\n\nPay / Benefits\n• Lead end-to-end production-grade ML lifecycle for credit risk models\n• Design and implement advanced risk modelling frameworks (e.g., decisioning, pricing, fraud)\n• Develop data-driven credit policies and lending strategies to expand addressable market\n• Ensure statistical rigor and guard against data leakage and bias\n• Translate model performance into business trade-offs for leadership (revenue vs. loss)\n• Set coding standards, perform code reviews, and mentor junior team members\n\nTasks\n• 4+ years of Data Science/ML experience with production-grade systems\n• Advanced knowledge of predictive modeling and credit risk concepts (IV, ROC AUC, SHAP)\n• Proficiency in Python and SQL; experience with modern monorepos and tools (Snowflake, dbt, ZenML, Dagster, Weights & Biases)\n• Ability to leverage AI/LLMs to improve outputs\n• Deep understanding of credit risk metrics (PD, EAD, LGD, EL) and risk-growth trade-offs\n• Strong communication skills to convey risk strategy to non-technical stakeholders\n\nKey requirements\n• 25 days of paid annual leave\n• private healthcare\n• life insurance\n• critical illness cover\n• pension plan\n• equity scheme",
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