Model Development and Deployment:
· Design, build, and deploy machine learning models for credit scoring, risk assessment, fraud detection, and customer segmentation.
· Calibrate model parameters and optimise existing business logic and parameters
· Ensure models are robust, interpretable, and provide actionable insights.
Data Analysis and Insights:
· Conduct thorough data analysis to identify trends, patterns, and opportunities to enhance existing scorecards and processes.
· Develop and maintain dashboards and reports to track model key performance metrics and provide actionable insights to stakeholders.
Model Infrastructure and MLOps:
· Develop and maintain model infrastructure to support the lifecycle of machine learning models from development to production.
· Automate workflows for model training, validation, deployment, testing and monitoring to ensure efficiency and reliability.
Mentorship and Leadership:
· Mentor and provide guidance to junior data scientists and analysts in the team.
· Lead data science projects from inception to completion, ensuring timely delivery and alignment with business goals.
Requirements:
· 5+ years of experience in data science, preferably within the fintech or financial services industry.
· Proven experience in developing and deploying machine learning models in a production environment.
· Strong background in statistical analysis and machine learning.
· Expert in credit modelling and risk management would be an added advantage
