Data Science Expert for Credit Risk Modelling
hace 1 mes
The Data Science Expert for Credit Risk Modelling will play a key role in driving innovation in credit risk modelling. The ideal candidate will have advanced proficiency in Python and experience with machine learning libraries, specifically for building predictive models in Credit Risk and Lending. The successful candidate will lead the development of predictive models for Credit Risk and Lending, using advanced machine learning techniques and Python in a GCP environment to optimise decision-making and risk assessment. This role requires excellent communication and collaboration skills, with the ability to work closely with data engineers, analysts, and business stakeholders to translate complex data insights into actionable business strategies.
Responsibilities:- Drive innovation in credit risk modelling by identifying opportunities for improvement, experimenting with new methodologies, and continuously refining models to enhance accuracy and performance.
- Lead the development of predictive models for Credit Risk and Lending, using advanced machine learning techniques and Python in a GCP environment to optimise decision-making and risk assessment.
- Leverage Large Language Models (LLMs) to process and analyse unstructured data, enhancing insights and improving credit risk modelling processes.
- Collaborate with Data Engineers and Data Analysts to design, build, and deploy scalable data solutions, ensuring seamless integration of models into production and effective delivery to business stakeholders.
- Mentor and guide junior Data Scientists, providing technical leadership, reviewing code and models, and fostering their growth and development within the team.
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