Description

Job Description

 
·         Build scorecards using ML algorithms (e.g. Random Forest, Gradient Boosting, XGBoost, Deep Learning) related to Credit Risk, Fraud Risk, Chance of Approval, Portfolio Management, etc.
·         Closely coordinate with other functions such as Product, Technology and Risk and align on business and technical needs
·         Identify optimization / automation opportunities in model development process such as Documentation, Turnaround Time (TAT), etc.
·         Liaise with Data and Systems teams to deploy ML solutions quickly and accurately
·         Analyze credit reports, financial statements for underwriting assessments.
·         Manage credit functions while deploying Credit Risk policies and risk Strategies for credit
·         Participate in strategic initiatives for monitoring legal and technical reports for credit recommendations

Requirements

·         Bachelors or any other educational qualification in disciplines such as Computer Science, Statistics, Economics, Mathematics, Business Administration, etc.
·         Domain expertise in Risk Management and / or Credit Risk domain is must
·         5+ years of working experience in data analytics, e.g. Data Processing, Model Development / Validation, Scorecard Implementation and / or Strategy formulation
·         At least 3+ years of hands-on experience of model development using tools such as R, Python, SAS, SQL, etc.
·         Strong analytical and logical skills with emphasis on relating ML insights with business intuition
·         Ability to take project ownership and innovate as and when required
·         Domain expertise in Risk Management and / or Credit Lending domain is preferred

Key Skills
Education

Any Graduate

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