Senior Data Scientist (Credit Risk Modelling)

** - Lead analytics initiatives across risk, marketing, and business strategy - Provide analytical solutions using statistical modeling and machine learning - Monitor, maintain, and enhance credit risk scorecards - Conduct advanced analytics to reduce portfolio losses - Build and deploy predictive models for lending decision areas - Collaborate with Product, Sales, and Risk teams to understand needs and build solutions - Design early warning systems based on segmentation and real-time analytics - Support offer generation and distribution using data insights - Liaise with IT & Credit teams and external vendors for analytics use-cases - Own the delivery of pricing models, risk strategies, and propensity analytics **

** - Minimum 4 years of experience in data analytics, with a preference for the financial industry - Proficiency in coding languages such as SQL, R, Python, and PySpark - Strong foundation in classical statistical techniques including Regression, Logistic Regression, Clustering, Dimensionality Reduction, etc. - Proven experience in credit risk modeling, including acquisition, behavior, and collections scorecards - Hands-on experience with Machine Learning algorithms such as KNN, Naive Bayes, Decision Trees, CART, Boosting & Bagging models, SVM, Neural Networks, Ensemble models - Experience working with large-scale datasets and performing deep root cause analysis - Strong verbal and written communication skills You will have the opportunity to work in a fast-paced environment with exciting stock options, a variable pay structure, and fast-track growth opportunities based on your performance and the company's growth. The sky is the only limit in this dynamic role!