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:
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
both predictive and prescriptive machine learning models that will assist with increasing strategic and and recommendations based on data analysis and modeling concluded and where relevant with knowledge and
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
and experience in NLP methods and customized NLU models. NLP/NLU Technology Integration Assisting with responsibilities assigned in the Agile Working Model (AWM) Charter C#, Python, SQL, PL/SQL HTML, JavaScript
validation and verification Techniques. Develop models to transform data from source to target for analytical