Responsibilities

- Develop credit risk models, scorecards, and portfolio risk models.
- Apply statistical, supervised, and unsupervised ML techniques.
- Build PD, LGD, and ECL models aligned with Basel II and IFRS9.
- Process large datasets and engineer credit bureau features.
- Optimize models for production with strong explainability and governance.
- Collaborate with business, product, and engineering teams.
- Research current ML/AI techniques and mentor junior team members.

Requirements

- Experience in Data Science, ML, or Risk Analytics.
- Strong experience in credit risk modeling, scorecards, Basel II, IFRS9, PD, LGD, and ECL.
- Proficiency in ML, statistical modeling, PCA, K-means, and XGBoost.
- Experience with deep learning, GenAI, RAG, and agentic AI frameworks.
- Knowledge of prompt engineering, RLHF, and LLM evaluation.
- Strong understanding of model governance, explainability, and responsible AI.

📌 Applied Data Scientist (Noida)
🏢 Recruito
📍 Noida