Credit Data Modeling Specialist

Banco Mercantil

. Lead the development, validation, implementation, and monitoring of statistical and Machine Learning models applied throughout the credit lifecycle, including Credit Score, Behavior Score, PD, LGD, EAD, Collection Scoring, propensity models, and credit limit models.

Posted 9/30/2026full-timeBelo Horizonte • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and monitoring statistical and Machine Learning models for credit and risk applications, with a strong focus on model evaluation metrics and compliance with regulatory standards. Proficient in translating analytical insights into actionable business strategies while collaborating effectively across teams.

Highest-signal resume keywords

Statistical ModelingMachine LearningCredit ScoringPythonSQL

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Hard Skills

Statistical ModelingMachine LearningCredit ScoringBehavior ScoringLogistic RegressionXGBoostRandom ForestNeural NetworksModel Evaluation MetricsData Analysis

Soft Skills

CollaborationAnalytical ThinkingCommunication

Industry Keywords

Credit RiskPDLGDEADCredit LifecycleBacenIFRS 9

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Lead the development, validation, implementation, and monitoring of statistical and Machine Learning models applied throughout the credit lifecycle, including Credit Score, Behavior Score, PD, LGD, EAD, Collection Scoring, propensity models, and credit limit models.
Develop predictive models using statistical and Machine Learning techniques, evaluating different approaches to enhance model discrimination and predictive power.
Conduct cut-off and risk-return trade-off studies, translating model results into recommendations and rules applicable to credit policies.
Collaborate with Credit, Risk, Data, and Business teams, connecting analytical results to origination strategies and portfolio management.
Evaluate and incorporate alternative data, credit bureau information, and new data sources to enhance models.
Monitor model performance and stability in production, tracking metrics such as KS, Gini, AUC, PSI, and CSI.
Identify degradation, performance deviations, and changes in portfolio behavior, proposing model recalibration, retraining, replacement, or enhancement.
Participate in model backtesting, calibration, and validation processes, ensuring robustness and compliance with business and regulatory requirements.
Drive the continuous improvement of modeling techniques, tools, and methodologies used by the department.

Requirements

What you’ll need

Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Physics, Economics, or a related field.
At least 5 years of experience developing, implementing, and monitoring statistical and/or Machine Learning models applied to Credit and Risk.
Practical experience with Credit Scoring, Behavior Scoring, Collection Scoring, credit risk, PD, LGD, EAD, or credit limit models.
Advanced proficiency in Python and/or R.
Advanced knowledge of SQL.
Proficiency in modeling techniques, including Logistic Regression, XGBoost, Random Forest, and Neural Networks.
Knowledge of model evaluation and monitoring metrics such as KS, Gini, AUC, PSI, and CSI.
Knowledge of the credit lifecycle, as well as credit origination and management policies.
Ability to translate analytical results into actionable insights for business decisions.
Knowledge of models and methodologies related to Bacen and IFRS 9.

Benefits

Comp & perks

Meal and food allowance (if preferred, both amounts can be provided on a single meal card)
Health insurance
Dental insurance
Childcare assistance
Life insurance
Private pension plan
Wellhub
Mercantil Development Academy
Profit Sharing (PLR)