Designing and deploying new decision processes using statistical and machine learning methodologies to improve lending decisions
Research and build innovative new attribute solutions to enable scalable risk assessment and decisions
Building and deploying optimization and machine learning models to diversify credit portfolio and minimize risks
Building and deploying credit risk monitoring, collection and pricing models.
Guidance to team members and providing technical support when its necessary
Qualifications:
Master’s degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline (Bachelors’ degree with significant relevant experience will be considered)
Work experience: Minimum 3 years of work experience in the relevant field
Experience in credit scoring and risk modelling techniques.
Proven experience in employing analytics solution on real world problems
Proven deep experience with SQL and Python
Experience in Linux, object-oriented programming and version controlling
Strong problem solving and decision-making skills
Commercial awareness and ability to understand broader business issues