Lead-Model Developer.Risk management - ERM

Mashreq Global Services

4 - 5 years

14 - 19 Lacs

kolkata mumbai new delhi hyderabad pune chennai bengaluru

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Skills Required

erm visual basic project finance sas data management model development data quality risk management wholesale python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Wholesale Risk Model Development

Strong foundation in Statistics and Mathematics.
At least 4-5 years of banking experience, out of which 1-2 years are spent in related areas
Strong analytical skills and knowledge on Financial Risk Management
At least 2-3 years of banking experience in related areas
Excellent computer skills (especially R, Python, SAS, Excel, Visual Basic, SQL & Oracle)
Postgraduate or professional qualification in risk management or finance such as CFA, FRM, PRM.
Experience of developing teams in a multi-jurisdictional and matrixed organization.
Understanding and experience of BCBS frameworks, CBUAE regulations relating to model management standards.

Technical & Delivery Responsibilities

Support the data preparation and model development, validation, and lifecycle management of Wholesale Rating Models
Support model development and validation including:
Corporate/Wholesale Rating Models including Large Corporate, Mid Corporate, SME, Sovereign, FI, HNWI, Project Finance, and Specialized Lending
Explore new approaches for rating model development for low default portfolios
Master Rating Scale (MRS) calibration

Wholesale Model Monitoring

Outline the goals of model monitoring, considering factors like accuracy and other relevant metrics based on the model purpose
Determine the expected performance of the respective models on historical data
Implement monitoring tools to continuously assess model performance. This includes monitoring input data quality, predictions
Communicate the model performance to relevant stakeholders to ensure the prompt attention to potential problems.
Regularly review and improve the model performance process based on the feedback, change in underlying data and evolving business requirement.

Data Management

Lead end-to-end data lifecycle management for model development, including sourcing, profiling, transformation, and documentation.
Identify data requirements for model development.
Coordinate with IT and data engineering teams to streamline data pipelines required for model development

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