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Data Scientist - NPL & Unsecured Portfolios

Anonymous
London
3 days ago
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We are working with a growing consumer finance fintech platform, who are looking to build out their Data and Analytics department. The team, who have recently received backing from a global Investment firm are now building out a Data and Analytics team in London - with a focus on supporting their Unsecured NPL Portfolio Investment team.


This role is ideal for a technically strong, quantitatively minded professional with a background in statistics and data science, looking to apply their skills in financial services. While specific NPL experience is not required, a passion for large-scale data analysis and modern analytics frameworks is essential.


You will work in a neo-bank/fintech-style environment, using cutting-edge technology to analyze terabytes of data and support high-impact investment decisions.


Responsibilities:

  • Develop, implement, and validate statistical and machine learning models for analysing non-performing loan portfolios.
  • Collaborate with cross-functional teams—including credit, collections, and data engineering—to translate business objectives into robust analytical solutions.
  • Build software using modern technology to enable investing and asset management at scale.
  • Apply Bayesian modelling and probabilistic programming techniques to address uncertainty and improve prediction accuracy.
  • Analyse large-scale datasets to identify key drivers, trends, and early warning signals within NPL portfolios.
  • Clearly communicate model results, insights, and recommendations to stakeholders, including both technical and non-technical audiences.
  • Stay current with advances in statistical modelling, machine learning, and data science, continuously evaluating and integrating new techniques and tools.


Requirements:

  • University degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred.
  • Strong expertise in statistical modelling, Bayesian inference, and machine learning.
  • Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan)
  • Experienced in SQL. Ability to write efficient and robust queries.
  • Demonstrated experience working with large and complex datasets.
  • Ability to communicate complex analytical concepts clearly and effectively to a range of audiences.
  • Experience with model governance, documentation, and deployment best practices.
  • Experience with cloud environments (e.g., AWS Sagemaker).
  • Experience with collaborative development tools (e.g., Git, JIRA) is a plus.
  • Prior experience in financial services, banking, or credit risk modelling is beneficial.
  • 5-8 years experience in a Data/Analytics role, ideally within a Financial Institution


Why This Role

  • Opportunity to build an analytics function from the ground up in a cutting-edge, entrepreneurial environment.
  • Work with massive datasets and modern tools at the forefront of fintech innovation.
  • High-impact role directly contributing to investment and portfolio decision-making.

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