documenting and enhancing a range of predictive models across the entire credit life cycle. Responsibilities: in the development and application of predictive models across the entire credit life cycle. Conduct continuous research aimed at identifying predictors and enhancing model development practice and techniques. Monitor and Analysis, Data Science, Machine Learning, Predictive Modelling, Problem Solving & Analytical, Python Programming Understanding & knowledge of predictive modelling practices, performance standards & methodologies
scorecards, frameworks and algorithm tuning Expose models and scorecards to other systems (API/Queue) Schedule (automation) Ability to identify the most relevant modelling approach based on the type of problem and available random forest, etc) Ability to train and maintain models Data cleaning and pre-processing (Size, data distribution including raw data) Experience in correctly applying model performance approaches in the context of the training training approaches taken (Classification Models, Confusion Metrix, etc) Qualifications & Experience:
Responsibilities: Demonstrate expertise in data modelling Oracle SQL Exceptional analytical skills analysing API's is a bonus Knowledge of the Agile Working Model Qualifications and Experience: Relevant IT / Business Build/Pipeline CloudFormation Technical data modelling and schema design (“not drag and drop”) Kafka
or B.Sc. (Informatics) - Essential Dimensional modelling and/or relevant Microsoft certification – Advantageous Proven data modelling techniques (3 years) Experience in Ralph Kimball data warehouse modelling (3 years)
to develop data models and pipelines for research, reporting, and machine learning Model front-end and analysts and BI analysts for reporting. Develop models that can be used to make predictions and answer
marts Experience in Data Vault and Dimensional modelling techniques Experience working in a high availability Wherescape RED SQL Server Data Vault modelling Dimensional modelling Transact SQL Automation/Scheduling
understanding of dimensional models. Conventional database- and data warehouse modeling skills, in order to understand understand the data warehouse data models. Terra Data QlikView Power BI SQL Server The Reference Number
functions) Knowledge and experience of data warehouse modelling methodologies Experience in using MS SSIS and designing solutions and good knowledge of data modelling concepts Experience of working in a team following
data analysis, machine learning, and predictive modelling Proficiency in programming languages such as Python relevant to business objectives Develop predictive models and machine learning algorithms to forecast customer
support high performing ML algorithms, predictive models and support real-time data visualisation requirements Agile methodology Knowledge of retail industry data models Advanced knowledge of compliance and IT governance