Manager, Credit Scoring
The role holder will be
responsible for the design, development, implementation, and monitoring of
credit scoring models. Further, the application of advanced analytics
techniques such as predictive and prescriptive modelling, advanced statistical
analysis, data mining, data visualization and machine learning to support the
management of credit risk within the organization.
Key Responsibilities
Design,
development and maintenance of credit scoring models for use in core banking
products as well as digital lending.
Full
ownership of the model development process from conceptualization through data
exploration, model selection, validation, implementation, and business user
training and support.
Work
closely with stakeholders to ensure adequate understanding of risk models and
their application. Play a key role in the development of products that rely on
credit scoring by providing analytics support in the design of product business
rules and strategies.
Work
with stakeholders throughout the organization to identify opportunities for
leveraging data to drive business solutions using Advanced Analytics for the
management of credit risk.
Development
and validation of risk models for use in Loan Pricing, Provisioning, Stress
Testing, ICAAP and other applications.
Understand,
measure and manage model risk.
Assess
the effectiveness and accuracy of new data sources, data governance activities
(e.g. data quality and cleansing strategies) data gathering techniques and
develop processes and tools to monitor, analyze and tune model performance and
data accuracy.
Work
with both structured and unstructured data including transforming of large,
complex datasets into pragmatic and actionable insights.
Develop
and maintain user and technical documentation/manuals on business requirements,
data sources, ETL related activities, data quality assessment, data cleansing
activities, data mining analyses, models developed, reports generated and
statistical solutions developed and deployed.
Stay
abreast of industry and regulatory trends that may impact new and existing
strategy development.
Qualifications
For the above position,
the successful applicant should have the following:
A
bachelor’s degree in mathematics, Business, Statistics, Economics, Actuarial
Science, Computer Science or equivalent combination of education and experience.
Proficient
in SQL, R, Python, Supervised and Unsupervised Machine Learning Techniques.
At
Least 5 years of proven performance in Data Science & Statistical Analysis.
Broad
understanding of the credit risk management process with at least 3 years’
experience in credit/risk management
Experience
in the use of Machine learning algorithms and techniques like supervised and
unsupervised machine learning, clustering, neural networks, reinforcement
learning, decision trees, regression, and adversarial learning.
Have
extensive statistical analysis and/or data science experience utilizing R,
Python and/or similar programming languages in manipulating data and drawing
insights from large data sets.
Be
an authority in querying and extracting large datasets from various sources for
use in the development of credit scoring models and reporting.
Excellent
team collaboration, verbal, written, and data presentation skills.
Flexible
and capable of handling multiple tasks in a fast paced, high-volume environment.
Have
an inquisitive nature with an aptitude to diagnose and tackle analytically
complex business problems.
How
to Apply
The above position is
a demanding role for which the Bank will provide a competitive remuneration
package to the successful candidate. If you believe you can clearly demonstrate
your abilities to meet the criteria given above, please log in to our Recruitment
portal and submit your application with a detailed CV.
To be considered your
application must be received by Monday 29th May 2023
Qualified candidates with
disability are encouraged to apply.
Only short-listed
candidates will be contacted.
