This role is for one of Weekday’s clients Min Experience: 2+ years

Location: Bengaluru

JobType: full-time Requirements Key Responsibilities 1. Risk Modeling & Business Impact Build and deploy models for: Probability of Default (PD) Loss Given Default (LGD) Exposure at Default (EAD) Fraud detection and capture rate optimization Translate business problems into measurable ML objectives and target variables Drive improvements in risk decisioning, underwriting, and collections strategies 2.

Machine

Learning & Model Development Develop scalable ML models using: LightGBM, XGBoost, CatBoost Random Forest, CART, Logistic Regression Work extensively on tabular datasets (structured financial data) Build ensemble and stacking models for improved performance 3.

Feature

Engineering & Model Evaluation Perform advanced feature engineering using: Weight of Evidence (WoE) Information Value (IV) Variable Clustering (VarClus) Evaluate models using: AUC-ROC / Gini coefficient F1 Score, Precision, Recall Handle class imbalance using: SMOTE Class weighting Threshold tuning 4.

Model

Optimization & Explainability Optimize models using:



Grid Search / Random Search Bayesian Optimization (Optuna preferred) Ensure model interpretability using: SHAP values LIME Partial dependence plots Communicate model insights effectively to business and risk stakeholders 5. Data Engineering & Pipeline Development Process large-scale datasets using: SQL (advanced level mandatory) PySpark / Hive / distributed systems Build robust data pipelines for model training and deployment Work with large transactional or bureau datasets Required Skills &

Experience : Must-Have - 2 - 5 years of relevant experience in credit risk / fraud analytics

- Solid hands-on experience with:
- Python (Pandas, Scikit-learn)
- SQL (complex queries, optimization)
- Expertise in tree-based models (XGBoost/LightGBM)
- Experience with imbalanced datasets in financial use cases
- Strong understanding of model evaluation metrics beyond accuracy Good to Have : Experience with: PySpark / distributed computing Credit bureau / transactional datasets Fintech / NBFC / banking domain Good-to-have skills Machine Learning, Credit Risk, Credit Risk Management

📌 ML Engineer (Bengaluru)
🏢 Weekday AI
📍 Bengaluru