Assistant Manager - Data Science

LatentView Analytics Ltd.; Bengaluru; In loco; INR 1.500.000 - 2.500.000; Tempo pieno

Descrizione del lavoro

Darwinbox Digital Solutions Pvt. Ltd. in Bengaluru seeks a senior credit risk analytics expert to lead development of credit card portfolio risk models, PD/LGD, and IFRS 9/CECL alignment.

The role demands hands-on experience with application and behavioral scorecards, data sourcing from bureau and internal signals, model governance, and strong communication for documentation and stakeholder collaboration.

Competenze

• Experience in building Application and Behavioral Scorecards.
• Strong exposure to PD, LGD, and EAD modelling.
• Familiarity with IFRS 9 / CECL frameworks and Lifetime ECL.

Mansioni

• Build statistically robust Application and Behavioral Scorecards; PD, LGD, and EAD models.
• Design loss forecasting frameworks using Vintage Analysis and Markov models.
• Engineer features from bureau, internal behavioral, and transaction data with data quality checks.
• Perform model calibration, backtesting, stability monitoring, discrimination analysis, and calibration testing.
• Explainability via reason codes and SHAP; conduct bias checks and challenger models.
• Align risk models with IFRS 9/CECL and Basel PD/LGD/EAD concepts.
• Develop credit card portfolio optimization models to drive growth.

Conoscenze

Credit Risk Analytics

Credit Card Portfolio Management

PD/LGD/ EAD models

IFRS 9 / CECL

Model Governance

Python

SQL

SAS

Machine Learning

Tableau

Strumenti

Python

SQL

SAS

Tableau

Machine Learning

Descrizione del lavoro

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.

Strong 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

Strong problem solving skills and communication