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Senior Credit Risk Data Scientist

Wayflyer· Technology
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Hybrid (London)Full-timePosted 7mo ago

About the role

Senior data science role focused on end-to-end credit risk modelling with production-grade ML, responsible for modelling frameworks, policies and risk strategies to optimize P&L while ensuring scientific integrity and robust code quality.

Responsibilities

  • Lead the end-to-end build of credit risk models, treating ML as software engineering so everything you ship is fast, reproducible and robust.
  • Design modelling frameworks for decisioning, pricing and fraud that move company-wide P&L, not just a dashboard metric.
  • Build credit policies and lending strategies that expand our addressable market safely, pushing conversion and profitability up together.
  • Ensure scientific integrity: statistically significant improvements, no data leakage, no bias hidden in the numbers.
  • Translate technical findings into business trade-offs for leadership, mapping ROC AUC to revenue and loss, and set code quality standards (reviewing, mentoring, contributing to libraries).

Qualifications

  • 4+ years building and maintaining production-grade ML systems
  • Deep understanding of credit risk concepts (PD, EAD, LGD)
  • Strong grip on predictive modeling and credit risk concepts (IV, ROC AUC, SHAP, PD, EAD, LGD, EL)
  • Comfort with Python, SQL, Snowflake, dbt, ZenML, Dagster, Weights & Biases
  • Experience in automated lending, price sensitivity modelling or CLV is a strong plus
  • Ability to communicate ROC AUC and business impact to stakeholders

Skills

Required:Credit risk concepts (PD, EAD, LGD)IV (Information Value)ROC AUC interpretationPythonSQLSnowflakedbt
Nice to have:SHAPZenMLDagsterWeights & Biases

Benefits

  • 25 days off, plus public holidays
  • Private healthcare
  • life insurance
  • pension
  • Equity
  • Generous parental leave for primary and secondary caregivers
  • 60 days a year to work abroad from wherever you want
Last updated Sep 17, 2026. Interested? Apply on the company site.
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