Very positive knowledge of statistical techniques such as clustering, segmentation, ranking, correlation, or regression etc.
Use sophisticated statistical techniques to develop scorecards, customer segmentation schemes, profiles, and other analytically based tools in day-to-day operations.
Ability to recognizing information and patterns in data that are not obvious, and focusing analytical efforts in pursuit of explanations, isolations of cause and effect.
Accountabilities:
Provide analytical support for different types of modelling tasks and projects, including model developments.
Work independently on variety of analytical tasks and projects during the production of model monitoring report, validations, and collaborations.
Work on projects to support initiative across decision science.
Work and build wrap rapport with business contacts, communicating analysis clearly and delivering out to agreed plans and time scales.
Take ownership and provides technical leadership to more junior analysts in the team.
Support model implementation and testing.
Comply with policies and apply best practises to all aspects of work.
Deputise for manager when required.
Act in line with the groups value and behaviours
Preferred candidate profile
Degree with quantitative content or equal skills derived from experience.
Experience extracting, manipulating, and drawing insight from the data
Experience of working on design, development, and validation of credit risk models
excel SAS, SQL, or similar experience
demonstrates initiative and problem-solving skills
valuable organisational and project management skills and ability to deliver tasks and project to deadlines
good written and verbal communication and presentation skills and ability to build report with the stakeholders to suggest the solution and communicate the impacts
*positive knowledge of the fundamental principles of banking credit Risk man