Develop and implement credit risk models to assess borrower risk and optimize portfolio performance.
Design and execute fraud detection models and analytics frameworks to identify suspicious activity.
Conduct forecasting and predictive analytics to support business strategy and risk management.
Translate complex data into strategic insights for business stakeholders.
Work with cross-functional teams to provide actionable recommendations for credit policy, fraud prevention, and risk strategies.
Perform data extraction, cleaning, and analysis using SQL Server and Python.
Continuously monitor model performance and recalibrate as necessary.
Support regulatory and compliance requirements by documenting models and Skills & Qualifications :
Bachelors / Masters degree in Statistics, Mathematics, Economics, Computer Science, or
related field.
4 - 7 years of experience in credit risk modeling, fraud analytics, or predictive modeling.
Strong proficiency in Python (data analysis, modeling libraries) and SQL Server.
Deep knowledge of statistical modeling, forecasting, and machine learning techniques.
Experience in developing credit scoring, PD / LGD / EAD, or fraud detection models.
Excellent problem-solving and analytical skills with attention to detail.
Strong communication and presentation skills for stakeholder management.
(ref : hirist.tech)
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Data Scientist • Gurugram
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