Data Scientist

Responsibilities:

1. Design, build, and deploy machine learning models for credit scoring, risk assessment, fraud detection, and customer segmentation.
2. Calibrate model parameters and optimise existing business logic and parameters.
3. Ensure models are robust, interpretable, and provide actionable insights.

Model Development and Deployment:

1. Design, build, and deploy machine learning models for credit scoring, risk assessment, fraud detection, and customer segmentation.
2. Calibrate model parameters and optimise existing business logic and parameters.
3. Ensure models are robust, interpretable, and provide actionable insights.

Data Analysis and Insights:

1. Conduct thorough data analysis to identify trends, patterns, and opportunities to enhance existing scorecards and processes.
2. Develop and maintain dashboards and reports to track model key performance metrics and provide actionable insights to stakeholders.

Model Infrastructure and MLOps:

1. Develop and maintain model infrastructure to support the lifecycle of machine learning models from development to production.
2. Automate workflows for model training, validation, deployment, testing and monitoring to ensure efficiency and reliability.

Mentorship and Leadership:

1. Mentor and provide guidance to junior data scientists and analysts in the team.
2. Lead data science projects from inception to completion, ensuring timely delivery and alignment with business goals.

Requirements:

1. 5+ years of experience in data science, preferably within the fintech or financial services industry.
2. Proven experience in developing and deploying machine learning models in a production environment.
3. Strong background in statistical analysis and machine learning.
4. Expert in credit modelling and risk management would be an added advantage.