You will develop and deploy machine learning scorecards to manage credit and fraud risk.
Responsibilities
Build scorecards using machine learning algorithms including Random Forest, Gradient Boosting, XGBoost, and Deep Learning for credit risk, fraud risk, and portfolio management.
Coordinate with Product, Technology, and Risk functions to align technical development with business needs.
Automate model development processes, focusing on documentation and turnaround time.
Liaise with Data and Systems teams to ensure accurate and rapid deployment of ML solutions.
Analyze financial statements and credit reports for underwriting assessments and implement risk strategies.
Required Skills
5+ years of experience in data analytics, model development, validation, or strategy formulation.
3+ years of hands-on experience in model development using R, Python, SAS, or SQL.
Expertise in Risk Management or Credit Risk domains.
Proficiency in data processing and machine learning implementation.
Strong analytical skills with the ability to translate ML insights into business intuition.
Experience analyzing credit reports and financial statements.
Proven ability to take project ownership and manage credit functions.