Data scientist II at WesBank

Role Purpose

• This role is within WesBank Retail and supports the purpose by measuring expected and unexpected risk inherent in the portfolio and building trust with stakeholders and regulators by ensuring that capital and provisions are correctly determined and set.  The role also supports the business to identify the risk return drivers and influencing the setting of the budget and risk appetite.

Are you someone who:

• Has model development experience as well as, monitoring and optimisation of existing models.
• Has a strong knowledge of IFRS 9 and experience in Impairment modelling or validation.
• Understands how to work with big data and transform data to be suited for analytical insights.
• Interested in the relation between capital & provisions and financial reporting.
• Has strong technical skills with strong coding proficiency (preferably in SAS).
• Hard working individual that can work well under pressure.
• Able to translate business requirements into tangible, creative solutions with guidance.

We can be a match if you are:

• Curious & courageous – you’re driven by always wanting to know more and learn more and you’re brave enough to take action.
• Obsessed with mastery – you know what it takes to become good at what you do and are constantly pushing yourself to achieve this.
• A team player – you believe in the power of teams, building and leveraging your networks.
• Emotionally intelligent – you are able to connect with people to build trust.

As a #Changeable you will have access to:

• Opportunities to network and collaborate.
• Opportunities to innovate.
• Flexible working environment
• Focus on health and wellbeing.
• Coaches and mentors to help with your professional development.
• A very generous leave policy to cater for your individual needs.
• Preferential employee banking rates that include Vehicle and Home loans

Qualifications and Experience

• Minimum Qualification: B Degree in Mathematical Sciences, Statistics, Actuarial Science
• Preferred Qualification: Honours Degree
• Experience: A minimum of 3 years' relevant experience in a credit risk analytics environment.
• Deep domain knowledge and experience of IFRS 9 within credit risk analytics.