INTRODUCTION
To implement the modelling, analysis, data mining and machine learning efforts within the Financial Analytics team.
REQUIRED SKILL SETS
A completed 3-year Bachelor's degree or Diploma in Finance, Economics or Maths is a minimum requirement.
Minimum of 5 years’ experience in credit and risk, analytical and statistical analysis is essential.
Experience in leveraging tools such as SAS, SAS Enterprise Miner, R, PHP, Python, Hadoop & SQL to drive efficient analytics.
Working knowledge of data mining principles: predictive analytics, mapping, clustering, collecting data from multiple data systems on premises and cloud-based data sources.
Working knowledge of machine learning techniques, for example: Support Vector Machine, Naïve Bayes, K-Nearest Neighbours, K-Means, Random Forest, Dimensionality Reduction Algorithms, Deep Learning techniques and Gradient Boosting Algorithms.
Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.
Experience writing advanced SAS code statements, models, and macros.