##### Job Description :
providing customer centric data analytics, including alternative methods of
aggregating raw data (internal and external), which will ultimately influence
the way in which we view and act on customer behaviour and customer health,
i.e. identifying risks and opportunities; and
implementing the use of machine learning to challenge and improve predictive
modelling techniques, the available characteristic universe across the
customer life cycle and optimising segmentation to enhance model performance.
Solutions should satisfy customer centricity and digitisation objectives.
_**Minimum Qualifications**_
**Type of Qualification:** Honours Degree
**Field of Study:** Mathematical Sciences
Other Minimum Qualifications, Certifications or Professional Memberships:
Honours degree (with majors in Statistics / Applied Mathematics / Econometrics
/ Actuarial Sciences/Engineering)
3-4 years experience in advanced analytics, combined with sufficient knowledge
of products and customer behaviour in a financial services environment.
Experience with data mining and retail credit risk modelling. Communication
skills, in particular, communication of technical concepts to a non-technical
audience. Coding ability and experience to deal with big datasets (preferably
in SAS, R, Python or SQL). Some experience of machine learning modelling
techniques, with an understanding of underlying details and parameters. Good
analytical problem-solving skills.
_**Behavioural Competencies:**_
Generating Ideas
Examining Information
Exploring Possibilities
Examining Information
Developing Practical Approaches
_**Technical Competencies:**_
Scientific Reasoning (ScR)
Statistical Inference
Data Analysis
Data Integrity
Strategic Planning and Reporting
