Senior analyst - Model Validation (Risk)

Indusind Bank; Mumbai; On-site; INR 1,200,000 - 1,900,000; Full time

Job summary

IndusInd Bank seeks a candidate with strong experience in credit risk model validation and development. The role requires a solid quantitative background, familiarity with regulatory regimes, and expertise in PD/EAD/LGD modeling. Proficiency in Python/SAS/SQL/R and data visualization is essential.

Excellent communication and stakeholder management skills are expected. The candidate will work on model development/validation projects, perform rigorous analyses, and prepare high-quality reports for

Qualifications

• Strong in credit risk model development/validation methodologies.
• Quantitative background in statistics/economics/engineering or related field.
• Familiarity with major regulatory regimes (US RBI UK MAS etc).
• Experience with PD/EAD/LGD models from development or validation.
• Proficient in regression and ML methods (GBM/XGBoost/CatBoost/Random Forest).
• Time series skills (ARIMA/ARIMAX) desirable.
• Proficient in Python/SAS/SQL/R for analysis and modeling.
• Ability to analyze data, visualize insights, and mine data.
• Strong reporting, communication, and stakeholder management skills.

Skills

Credit risk model validation

Credit risk model development

Quantitative background

Regulatory regimes knowledge

PD (Probability of Default) models

EAD (Exposure at Default) models

LGD (Loss Given Default) models

Statistical modeling: Linear/Logistic

Machine learning: GBM/XGBoost/CatBoost

Random Forest

Time Series: ARIMA/ARIMAX

Python

SAS

SQL

R

Data analysis/visualization/mining

Report writing

Stakeholder management

Communication skills

Education

Bachelor's/Master's in Quantitative field

FRM/PRM/CFA desirable

Tools

Python

SAS

SQL

R

Job description

Desired candidate

Experience into Credit Risk Model Validation in MNC Banks / Private Sector Banks/ Other Foreign banks/ Public Sector banks / Consulting firms.

1. 1. Strong experience and practical in-depth understanding of Credit risk model development/validation methodologies and procedures.
2. 2. Strong quantitative background in Applied Statistics/Mathematics/Operations Research/ Economics /Engineering / or related quantitative field.
3. 3. Strong work experience and practical understanding of at least one or more of the following regulatory regimes: US (FRB/OCC), UK (PRA/ECB), CBUAE (MENA), RBI (India), MAS (Singapore), HKMA (Hong Kong).
4. 4. Strong work experience and/or in-depth practical understanding of Credit Risk models PD (Probability of Default), EAD (Exposure in Default), LGD (Loss Given Default) models from either model development or model validation standpoint.
5. 5. Sound work experience and good practical understanding of Statistical modeling techniques of Linear Regression, Logistic Regression; Machine learning approaches of Gradient Boosting (GBM), XGboost (Extreme Gradient Boosting), Cat-Boosting, and Random Forest. Time Series modeling knowledge approaches ARIMA, ARIMAX would be added plus.
6. 6. Highly proficient in statistical tools/ programming languages (viz. Python, SAS, SQL, R).
7. 7. Strong Experience with data analysis, data visualization, and data mining techniques.
8. 8. High quality Report writing skills from either Model Development or Model Validation perspective factoring the regional regulatory guidelines/framework and Standard Operating Procedures.
9. 9. Strong Critical reasoning skills and analytical capabilities for analyzing models and related modeling/Financial products analysis & exercises.
10. 10. Adept in Stakeholder Management and excellent in Oral and written communication skills as well as interpersonal skills.

Qualification

• Bachelors and/or Masters degree in Quantitative Finance/ Statistics/Operations-Research/Economics/Mathematics/Engineering or related quantitative fields.
• Risk Management qualifications such as FRM/PRM/CFA desirable though not mandatory.