Job Description:

- Strong experience in Credit Risk Analytics, with a focus on Credit Card Portfolio Management and Risk Modeling.

- Hands-on expertise in Application Scorecards and Behavioral Scorecards.

- Strong experience in developing and working with PD (Probability of Default) and LGD (Loss Given Default) models.

- Solid understanding of IFRS 9 / CECL frameworks, including Lifetime ECL and Staging.

- Strong knowledge of Model Governance and associated documentation requirements.

- Good understanding of the Credit Card Lifecycle and various stages of portfolio management.

- Hands-on experience with Portfolio Interventions and credit risk strategies.

- Robust knowledge of Credit Bureau Data and its application in risk modeling.

- Experience working with Behavioral Signals and Transaction-Level Spend Data.

- Proficiency in Python, SQL, SAS, Machine Learning, and Tableau.

- Strong analytical, problem-solving, and data interpretation skills.

- Excellent communication and documentation skills.

Responsibilities:

- Build statistically robust Application and Behavioral Scorecards, along with PD, LGD, and EAD models.

• Design and develop loss forecasting frameworks using Vintage Analysis, Roll Rate/Markov Models, Survival/Hazard Models,



and GLM/GBM techniques at both segment and portfolio levels.
• Engineer and validate features from bureau data, internal behavioral data, transaction data, device signals, and alternative data sources with strong data quality controls.
• Perform model calibration, backtesting, stability monitoring (PSI/CSI), discrimination analysis (KS/AUC), and calibration testing.
• Implement model explainability techniques such as reason codes and SHAP, along with bias/fair lending checks and challenger/benchmark model development.
• Align risk models with accounting and regulatory frameworks including IFRS 9/CECL and Basel PD/LGD/EAD concepts.
• Develop credit card portfolio optimization models to drive customer spend, engagement, and portfolio growth.
• Support portfolio spend growth initiatives through targeted segmentation, persona-based strategies, merchant targeting, and campaign recommendations to increase cross-border spend and customer engagement.

Skills:

ML, Data science, Risk Analytics

Strong problem solving skills and communication

Job Snapshot

Updated Date

02-10-2026

Job ID

J_5299

Location

Bengaluru, Karnataka, India

Experience

6 - 9 Years

Employee Type

Permanent

📌 Assistant Manager - Data Science (Bengaluru)
🏢 LATENTVIEW ANALYTICS
📍 Bengaluru