Role Description Develop financial and customerbehaviour models that guide the design forecasting and commercial management of the eBucks rewards programme The role combines quantitative analytics rewards economics and business judgement to balance customer value behaviour change and financial sustainability Responsibilities And Skills Build maintain and enhance customerlevel financial and behaviour models Model rewardrule valueproposition and partnership impacts including scenarios sensitivities and forecasts Support the annual Earn Rule Change lifecycle preanalysis modelling forecasting implementation support and testing Analyse customer and transactional data and convert findings into clear commercial recommendations Support budgeting cost management and customerlevel financial analysis Apply model governance through validation peer review documentation and quality assurance Automate repeatable work and develop reusable scalable analytical capabilities Technical Skills Strong SAS andor SQL Python or R advantageous Advanced Excel and strong PowerPoint capability Financial forecasting scenario modelling and customerbehaviour analytics Ability to manipulate large datasets translate business rules into model logic and improve existing processes Automation AIassisted analytics and visualisation experience advantageous Qualifications Experience Bachelors degree in Data Science Actuarial Science Statistics Econometrics Applied Mathematics Quantitative Finance Computer Science or a related quantitative field Honours or postgraduate qualification advantageous 3-5 years experience in data science financial modelling actuarial quantitative or commercial analytics Banking financial services loyalty or rewards experience advantageous CORE COMPETENCIES Quantitative problem solving and critical thinking Commercial and financial acumen Attention to detail and accountability for accuracy Robust stakeholder engagement and clear communication Proactive curious and continuousimprovement mindset Ability to work through ambiguity and tight delivery timelines