Transforming raw data into actionable insights, building predictive models, and supporting data-driven decision-making across the organization.
Review Scorecard Performance - Model Outcome Analysis, Assumptions and model limitation, back testing.
Inventory of Models, BRE rules for the model
Build statistical model for predicting ECL movement,
Model the portfolio performance of all products pre scorecard deployment and post scorecard deployment.
Build model for collection flows and estimation of portfolio performance.
Key Responsibilities
Analyze large datasets to identify trends, patterns, and opportunities for business growth and portfolio monitoring.
Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.
Collaborate with cross-functional teams to understand business requirements and translate them into data solutions.
Design and implement data pipelines and ETL processes.
Communicate findings through dashboards, reports, and presentations using tools like Power BI, Tableau, or Python visualizations.
Build statistical model / scorecards
Can do independent - statistical validation of scorecards
Analyse reason for portfolio movement - Highlighting key changes in portfolio (basis model performance)
Create model for predicting - various parameters - ED movement / Probable ED flows, Tracking Write Off movement, recovery trends and probable losses - modelling them for predicting future performance.
Mandatory Skills Required
Degree in Statistics / mathematics / economics with finance background will be an added advantage.
Prior experience of statistical modelling for 4-5 Years
Proficiency in python /R /SAS /MATLAB / & SQL
Desirable Skills
Excellent communication and problem-solving skills.
Strong understanding of statistical methods and data modeling.
Power BI, Tableau, or Python visualizations.
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