Credit Risk Modeling Specialist

Banco Bari

. Serve as the technical authority on statistical credit risk modeling, working strategically with the Business team in the Real Estate Credit division .

Posted 10/21/2026full-timeCuritiba • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical credit risk modeling, including the development and monitoring of models in production environments. Proficient in advanced statistical techniques and programming languages, with a strong focus on collaboration and communication with cross-functional teams.

Highest-signal resume keywords

Credit Risk ModelingStatistical TechniquesAdvanced PythonSQLMLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Credit Models DevelopmentFeature EngineeringModel MonitoringBacktestingLogistic RegressionGradient BoostingModel ExplainabilityBias MitigationStatistical AnalysisData Preparation

Soft Skills

CommunicationCollaborationPresentation SkillsProblem-Solving

Tools & Technologies

BigQueryGCPPandasScikit-LearnXGBoostLightGBM

Industry Keywords

Real Estate CreditCMN Resolution 4,966IFRS 9Independent Model ValidationLGPD Compliance

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Serve as the technical authority on statistical credit risk modeling, working strategically with the Business team in the Real Estate Credit division
Develop, validate, and enhance credit models (application, behavioral, PD, and LGD) for automated approval (fast-track)
Lead data preparation and feature engineering using internal and credit bureau data, ensuring quality and traceability
Monitor models in production (KS, Gini, PSI, and variable stability)
Conduct backtesting and define recalibration criteria
Optimize policies and cutoffs through vintage analysis, swap-in/swap-out analysis, and assessment of their impact on the conversion funnel
Support expected credit loss and provisioning methodologies aligned with CMN Resolution 4,966
Collaborate with Data Engineering, Product, Risk, and Sales teams to deploy models to production and translate business needs into solutions
Document methodologies for governance and audit purposes
Present results clearly to executive leadership

Requirements

What you’ll need

Proven experience in credit risk modeling, including the development, implementation, and monitoring of models in production environments
Strong command of statistical and machine learning techniques applied to tabular data, including logistic regression/scorecards (WoE, IV) and gradient boosting (XGBoost, LightGBM)
Advanced Python (pandas, scikit-learn) and advanced SQL
Experience working with large datasets in cloud environments, preferably BigQuery/GCP
Familiarity with model explainability techniques (e.g., SHAP), as well as bias mitigation and LGPD compliance
Ability to explain technical decisions and trade-offs to non-technical audiences
Degree in Statistics, Mathematics, Engineering, Computer Science, Economics, or a related field, or equivalent experience
Experience with real estate credit (home equity or mortgage lending) — a plus
Experience building models for decision engines and automated workflows — a plus
MLOps practices (version control, CI/CD, and model monitoring) — a plus
Knowledge of Bacen regulations, CMN Resolution 4,966/IFRS 9, and independent model validation — a plus
Knowledge of R or survival analysis techniques — a plus
Postgraduate degree or master’s degree in a quantitative field — a plus

Benefits

Comp & perks

Food Allowance
Meal Allowance
Transportation Allowance
Health Insurance (no monthly premium or copay for you and your dependents)
Dental Insurance (multiple plans and coverage options)
Wellhub: A comprehensive network of gyms, wellness, meditation, nutrition, and other apps
Profit-Sharing and Results Program (PLR)
Bariclube: Partnerships with restaurants, gyms, universities, language schools, and more
Bari Headhunter: Refer talented professionals and earn rewards!
Continuous learning environment
One-on-one meetings (feedback culture)
Performance reviews and Individual Development Plans (IDPs)