Sriyogaesh Arthanariswaran
Credit Risk Analyst @Cclyticx Services Private Limited
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WORK HISTORY
Credit Risk Analyst @Cclyticx Services Private Limited
Chennai, IN
Design, build, and independently validate credit-risk scorecards for a U.S. subprime credit-card lender, using SAS and Python with techniques such as logistic regression, XGBoost, and Random Forest to estimate Probability of Default (PD)• Perform data cleaning, WOE/IV transformation, and feature engineering to enhance predictive power and reduce model bias.• Conduct model performance testing using KS statistic, PSI, Gini, and AUC to track stability and accuracy across development, validation, and OOT datasets.• Designed and automated dashboards and reports to track private-label sales KPIs and portfolio performance, providing actionable insights for credit-strategy and risk-management decisions.• Partner with cross-functional teams (data engineering, business, and compliance) to implement risk strategies that improved portfolio delinquency rates and reduced credit losses.
EDUCATION
WorldQuant University
Master of Science - MS
National Institute of Technology Tiruchirappalli
Bachelor of Technology (B.Tech.)
SKILLS
ABOUT SRIYOGAESH ARTHANARISWARAN
A graduate of the National Institute of Technology, Tiruchirappalli with a B.Tech. in Metallurgical Engineering, currently pursuing an M.S. in Financial Engineering at WorldQuant University (expected 2027). Currently working as a Credit Risk Analyst at CClyticx Services Private Limited, contributing to the development and validation of credit-risk scorecards using advanced statistical and machine learning techniques like logistic regression, XGBoost, and Random Forest. Skilled in exploratory data analysis, PCA, and risk modeling, with additional expertise in data cleaning, feature engineering, and model performance testing. At CClyticx, contributed to designing and automating dashboards and reports that provided actionable insights for credit-strategy and risk-management decisions. Demonstrated commitment to enhancing model stability and accuracy through collaborative work on validation processes and performance tracking. Motivated by opportunities to apply technical expertise to real-world financial challenges and eager to bring analytical rigor, teamwork, and a solutions-oriented mindset to organizational goals.
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