DVP - Risk Analytics Lead

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Applied Mathematics, or a highly quantitative discipline from a premier institution
• 9-14 years of professional experience within data science, risk analytics, or quantitative risk management. Proven experience building predictive models, optimizing credit policies, and delivering complex analytical insights.
• Advanced mastery of SQL for complex data extraction, querying, and manipulation. Strong hands-on programming proficiency in Python or R for statistical analysis and machine learning.
• Deep conceptual and practical understanding of advanced statistical foundations, including descriptive analytics, experimental design, hypothesis testing, Bayesian inference, confidence intervals, and probability distributions.
• Proficiency with core machine learning techniques and statistical algorithms, specifically decision tree learning, ensemble methods (Random Forest, Gradient Boosting), logistic regression, and cluster analysis.
• Demonstrated competence in processing, cleanup, and engineering of large-scale datasets, with a proven ability to work with both highly structured financial databases and semi-structured/unstructured data sources.
• Deep functional knowledge of retail credit lines and secured credit products. Exposure to fintech lending ecosystems, retail banking, NBFC operations, or SME/LAP/secured lending is strongly preferred.