Design, develop, and deploy advanced predictive models and analytics to assess credit risk, optimise lending growth, and improve overall portfolio performance.
Work closely with cross-functional teams, including Risk Management, Product, Engineering, and Business Strategy, to identify opportunities for data-driven improvements and align solutions with business needs.
Monitor and analyse the performance of existing models and strategies, identifying areas for improvement and implementing data-driven refinements as needed.
Present complex data-driven insights and recommendations to stakeholders in a clear, concise, and actionable manner, while fostering a data-driven culture within the organisation.
Mentor and guide junior data scientists, fostering a collaborative environment and promoting the growth and development of the data science team.
Stay current with the latest trends and developments in data science, fintech, and credit risk management, continually exploring new methods and technologies to enhance the organisations capabilities.
Do you have the right
ingredients*
Advanced degree in quantitative field such as Data Science, Statistics, Mathematics, Financial Engineering or related discipline
8+ years of experience in data science, with a focus on credit risk modelling and lending growth strategies, preferably within the fintech lending space.
Proficiency in machine learning, AI, and statistical modelling techniques, with a strong track record of developing and deploying successful predictive models in a business setting.
Strong proficiency in Python and SQL and experience with data science libraries and tools such as: Spark, Scala, scikit-learn, Tensorflow, PyTorch, XGBoost etc.
Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, task orchestration (Airflow) and AWS tooling
Strong understanding of credit risk management, lending practices, and regulatory requirements within the financial industry.
Excellent communication and presentation skills, with the ability to articulate complex data-driven insights to both technical and non-technical stakeholders.
Strong leadership skills, with experience mentoring and guiding junior data scientist