Data Scientist (Credit Modeling Specialist

Description

Job Summary: We are seeking a Data Scientist / Credit Modeling Specialist to work in the Credit Policy area, developing analyses and statistical models for credit granting strategies. Key Highlights: 1. Develop statistical and predictive models applied to credit risk 2. Generate insights that directly impact credit policy 3. Identify opportunities for improvement in credit granting policies and strategies We are looking for a Data Scientist / Credit Modeling Specialist to work in the Credit Policy area, developing quantitative analyses and statistical models that support the definition and evolution of credit granting strategies. The professional will be responsible for generating insights, identifying opportunities for improvement in existing policies, developing statistical and predictive models to support credit granting, and simulating the impact of changes to credit policies—supporting decisions that balance growth, risk, and profitability. We expect someone who goes beyond descriptive analyses, contributing to model development, data-driven evolution of risk strategies, robust simulations for decision-making, and generation of insights that directly impact credit policy. **Key Responsibilities** * Develop statistical and predictive models applied to credit risk * Enhance existing models * Conduct portfolio behavior analyses * Perform impact simulations of changes to credit policies * Structure analytical datasets for modeling * Generate insights regarding credit portfolio behavior * Identify opportunities for improvement in credit granting policies and strategies * Build analytical dashboards for monitoring credit performance * Collaborate with Risk, Business, and Technology teams **Mandatory Technical Requirements** * Experience in statistical modeling applied to credit or risk * Programming in Python * Strong proficiency in SQL for handling large datasets * Experience with analysis and modeling libraries (e.g., pandas, scikit\-learn, statsmodels) * \-Knowledge of predictive modeling techniques (logistic regression, decision trees, boosting, etc.) * Experience in portfolio behavior analysis (vintage, roll rate, cohort) * Experience with visualization tools (Power BI, Tableau, or similar) **Desirable Credit Risk Knowledge** * Probability of Default (PD) modeling * Credit scorecards * Cutoff and segmentation strategies * Loss rate / NPL * Credit policy simulation * Credit granting strategy **Differentiators** Experience in financial institutions, fintechs, banks, or finance companies Experience in credit scoring development Experience in machine learning applied to credit risk Experience with credit decision engines Experience in model deployment or MLOps **Behavioral Profile** Strong analytical reasoning, investigative curiosity about data, ability to translate models into business insights, autonomy to conduct complex analyses, clear communication of technical results to business areas. Education: Statistics / Mathematics / Engineering / Data Science / Computer Science Hybrid work arrangement: 3 days per week onsite at client location (Berrini and Barueri areas), with the first month fully onsite. Remuneration to be defined \+ benefits