As of a team, you will participate in designing, developing, and deploying state-of-the-art, datadriven predictive models to solve business problems using the latest technologies in data mining, statistical modelling, pattern recognition, and performance inference.
• Designs and develops state-of-the-art, data-driven exploratory analysis as well as predictive and decision models to solve business problems.
• Builds and evaluates predictive and decision models to be deployed in production systems, or for research.
• This includes the analysis of large amounts of historical data, determining suitability for modeling, data clean-up, pattern identification and variable creation, selection of sampling criteria and performance definition, and variable selection.
• Experiments with different types of algorithms and models, analyzing performance to identify the best algorithms to employ.
• A graduate, ideally with a mathematical or statistical degree (or a degree with a high level of quantitative, statistical or operational research content) or relevant experience
• Expertise in credit risk management processes, organisation and risk policies. Strong expertise in the use of data manipulation and analysis
• Experience with credit risk model developments. Experience with fraud and marketing analytics a plus
• Knowledge of: Scoring technology and methodologies; Model development techniques and tools; Advanced statistical methods and quantitative analysis; Statistical tools and programs; Fluency in SAS, WPL, R, Python or other similar programming language.
• An excellent communicator with the ability to explain complex concepts and describe technical material to non-technical users