Requirements
· Bachelor’s degree in engineering (computer, electrical and electronics, industrial), statistics, mathematics. Master’s and PhD degree in related subject areas are preferable.
· At least 2 years experience in banking sector, especially Credit Risk departments (analytics or modeling)
· Expert knowledge on SQL, MS office and at least one programing language (R, Python, SPSS Modeler)
· Relevant project work experience in the areas of data science and machine learning
· Excellent analytical skills and strategic thinking, creative problem solver capabilities
· Strong data analysis, interpretation, data visualization skills and ability to communicate data insights
· Excellent interpersonal skills; ability to work across virtual teams
· Strong verbal and written communication skills in English
Role Description
· Manage and improve the process of data collection, ingestion, manipulation, and display for risk related reporting processes
· Develop and monitor risk based models (PD, LGD, EWS, credit risk acceptance criteria sets, limit optimization, etc.) by using machine learning algorithms for all business lines
· Lead the planning, development, and delivery of analytic projects from start to finish; includes all stages of project identification, stakeholder engagement, project management, and closeout
· Work closely and manage projects with several departments like IT, business, validation, etc.
· Maintain proficiency within the data science domain by keeping up with technology and trend shifts.