Key Responsibilities
Develops new models (e.g., propensity, churn, micro segmentation, contact-ability, response, etc.) for campaign analytics that deliver value and/or improve on prior model.
Builds models that are fit for purpose and operate within performance metrics.
Optimises future model performance (take up rate, environmental climate, business strategy, model drifts, etc.) against business strategy and actual model performance.
Stays abreast of new model development techniques and tools (e.g., Random Forests, CHAID, CART, etc.). Measures:
Successful test and learn iteration cycles.
Suggestions for techniques and changes to models.
Feedback from model production environment in Campaign Analytics
Feedback from model governance forum.
Delivery of high quality output, in budget and on time, with positive stakeholder feedback (done on a regular basis).
Qualifications
Type of qualification: Honours Degree
Field of study: Mathematical Sciences
Experience
Years: 3-4 Years
Experience Description: Experience in advanced analytics, combined with sufficient knowledge of products and customer behaviour in a financial services environment. Significant exposure to propensity, attrition, CRM and leads management, next-best action and segmentation models, as well as behavioural analysis.
Knowledge of Coding in Python, SQL advantageous
SAS Software knowledge
Basic understanding of technical tools used
Must have stable wi-fi connection
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