Minimum 5 years hands on experience in model building methodologies, implementation and compliance. Retail Risk Analytics, Credit Risk Modelling & IFRS9 Expert knowledge of credit scoring techniques, Reporting management & Meeting Deadlines Deep understanding of banking
Key Responsibilities Build, validate, and maintain machine learning models for forecasting, classification, regression, anomaly detection, and business analytics. Perform data cleaning, feature engineering, model evaluation, and performance monitoring to ensure reliable and scalable solutions. Develop data
Sr. Big Data (with AWS Certification) SME Job Requirements: 8+ years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field -
The role would be to support one or more databases of low to medium complexity with multiple concurrent users, ensuring control, integrity and accessibility of the data. Developing and maintaining enterprise data documentation and metadata models
Role Summary Senior Data Scientist focused on fraud strategy analytics and operational monitoring across a consumer lending portfolio. You will turn fraud data, scorecard performance, and decisioning outcomes into actionable policy, rule, and reporting recommendations —
Role Summary Senior data science leader who owns the strategy, roadmap, and delivery of the machine-learning and statistical models that power our consumer lending business. You will lead the development of credit risk models for underwriting
Role Summary Hands-on data scientist on the data science and model development team, focused on building the machine-learning and statistical models that power our consumer lending decisions. You will develop credit risk models for underwriting and