for the impairment and capital models (such as PD, LGD, and EAD models) and using IFRS9 standards. You
make a difference by providing input to the credit models.
Education:
frameworks and algorithm tuning
Qualifications
focus on Prescriptive Analytics and Predictive Modelling. ● Engage with internal business clients with ● Create algorithms and build machine learning models to enhance product offerings and solve business systems to track model performance. ● Presentation of data science opportunities and model outcomes to a ● Experience or familiarity with data science model operationalization on-prem or in the cloud (GCP
various economic modelling techniques (Input-Output modelling, multi-sector modelling, Cost Benefit Analyses Analyses, Socio-Economic Impact Modelling etc) Conduct relevant primary and secondary research using a econometric techniques (Input-Output modelling, multi-sector modelling, etc.) Experience in Socio-Economic
various economic modelling techniques (Input-Output modelling, multi-sector modelling, Cost Benefit Analyses Analyses, Socio-Economic Impact Modelling etc) Conduct relevant primary and secondary research using a econometric techniques (Input-Output modelling, multi-sector modelling, etc.) Experience in Socio-Economic
teams to understand business problems, develop models that drives automation, predictive analytics, advanced external data providers. Design and implement data modelling, data mining, and machine learning algorithms maintain predictive and prescriptive analytical models to support decision-making and drive business value and data transformation to prepare data for modelling and analysis. Utilize data visualization techniques audiences. Continuously evaluate and optimize existing models, algorithms, and data sources to improve accuracy
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:
reporting
execution that includes valuations, financial modelling, market and investment research and analysis etc M&A
integrity of data used in financial models • Create valuations models and formulate investment recommendations