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Job Summary: Experienced professional in developing and validating predictive models for credit, recovery, and offer propensity, using programming languages and advanced techniques. Key Highlights: 1. Development of predictive models for credit and recovery 2. Experience with Python, SQL, and SAS 3. Financial impact analysis and feasibility assessment of initiatives Description: * Experience in developing predictive models for credit granting and maintenance, credit recovery, or propensity to accept offers/contracts. * Experience with programming languages (Python, SQL, SAS). * Experience in developing feasibility studies and financial impact analyses of initiatives, policies, and strategies. * Familiarity with advanced predictive modeling techniques (Machine Learning, Deep Learning) is desirable. * Experience with Cloud Computing platforms (AWS or GCP) is desirable. * Knowledge of dynamics related to financial products (revolving credit, installment loans, and insurance) is desirable. * Develop, implement, validate, and monitor statistical models for forecasting credit risk, voluntary recovery of delinquent customers (Self\-cure), progression along the collections score scale (Collections Score), or propensity to accept product offers. * Identify and evaluate new information sources (macroeconomic time series, news bulletins, mobile device and digital channel interactions, voice data from customer service, etc.). * Identify and evaluate new systemic and analytical solutions for developing, parameterizing, and monitoring predictive models. * Perform backtests, validations, and customizations of scores and attributes provided by credit bureaus (scores, restrictions, positive credit registry, and open finance). * Conduct feasibility and impact studies of credit initiatives based on credit performance and portfolio profitability. 2511090202181588320
