Responsibilities

- Develop credit risk models, scorecards, and portfolio risk models.
- Apply supervised and unsupervised ML techniques, including XGBoost, PCA.
- Build risk models aligned with BASEL-II and IFRS9 standards.
- Estimate PD, LGD, and Expected Credit Loss (ECL).
- Process large datasets, perform EDA, and engineer features.
- Integrate credit bureau data and ensure data quality.
- Optimize models for accuracy, explain ability, and production use.
- Collaborate with business, product, and engineering teams.
- Research current ML techniques and mentor junior team members.

Requirements

- Experience in Data Science, ML, or Risk Analytics within BFSI/lending.
- Experience developing credit risk models and scorecards.
- Strong skills in statistical modeling and supervised/unsupervised ML.
- Knowledge of deep learning and financial risk applications.
- Familiarity with agentic AI, RAG, prompt engineering, and LLM evaluation.
- Understanding of model governance, explain ability, and responsible AI.
- Research, publications, or open-source contributions are a plus.

📌 Applied Data Scientist (Delhi)
🏢 Recruito
📍 Delhi