Credit Risk Modelling Specialist

1 month ago

London, Greater London, United Kingdom Aspire Data Recruitment Full time
Job Title: Credit Risk Analyst

Aspire Data Recruitment is seeking a skilled Credit Risk Analyst to join our team. The successful candidate will be responsible for designing, developing, and deploying state-of-the-art, data-driven predictive models to solve business problems using the latest technologies in data mining, statistical modeling, pattern recognition, and performance inference.

Key Responsibilities:
  • Design and develop data-driven exploratory analysis and predictive models to solve business problems.
  • Build and evaluate predictive models to be deployed in production systems, or for research, including data clean-up, pattern identification, and variable creation.
  • Experiment with different types of algorithms and models, analysing performance to identify the best algorithms to employ.
  • Assist with technical product support for new or existing products/services, including production of sales collateral or ad-hoc investigations initiated by internal or external clients.
  • Plan effectively to set priorities and manage projects, identify roadblocks, and work to get them removed.
  • Handle communication with internal and external clients as needed.
  • Determine appropriate model report format for communication with clients.
  • Participate in authoring white papers, proposals, and publications.
  • Mentor other scientists and assign modelling tasks when appropriate.
Requirements:
  • A graduate degree in a mathematical or statistical field, or a degree with a high level of quantitative, statistical, or operational research content.
  • Experience with an analytic solutions or consulting company, and preferably in a client-facing project management capacity.
  • Knowledge and experience in applying data to solve business problems through quantitative analysis, experience with predictive modelling and optimisation, and knowledge of the principles and practices of project management.
  • Experience with credit risk model developments, and experience with fraud and marketing analytics is a plus.
  • Strong statistical, data processing, and analytical skills.
  • An excellent communicator with the ability to explain complex concepts and describe technical material to non-technical users.
  • Knowledge of scoring technology and methodologies, model development techniques and tools, advanced statistical methods and quantitative analysis, statistical tools and programs, and fluency in SAS, WPL, R, Python, or other similar programming languages.

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