Senior Analyst, Lending Models

Overview

Hands-on modelling role within Allica Bank's Credit Portfolio Management team, building, implementing, monitoring and optimising IFRS9 impairment models and the decisioning models and policy rules behind automated lending.

What you'll do

• Take a hands-on role in the design, build, implementation and continuous refinement of the bank's credit risk models, spanning IFRS9 impairment models (PD, LGD, SICR and economic response) and statistical and machine learning models supporting automated lending decisions.
• Develop and deploy models in Python across the full model lifecycle, including data preparation, feature engineering, model fitting, validation, implementation and ongoing performance assessment.
• Perform ad-hoc analysis to optimise credit policy rules and decisioning flows, using rule-firing, decision and outcome data to identify redundant, overlapping or mis-calibrated rules.
• Produce regular monitoring covering population stability, discriminatory power, calibration, segment and vintage performance, decision rates and alignment with underwriting outcomes for decisioning models.
• Recalibrate or redevelop models as portfolio experience matures, comparing predicted and actual outcomes and adjusting model scaling, score cut-offs or policy thresholds where evidence of drift or mis-calibration exists.
• Lead root-cause investigations into model, rule or decisioning-flow underperformance by tracing issues through decision logs, data lineage, feature calculations, production pipelines and implementation logic.
• Build well-controlled, reproducible modelling processes and drive improvements to the data, tooling and infrastructure required for future model development and deployment.
• Document models, rules, assumptions, limitations and changes to a high standard, supporting governance, independent review and validation, and stakeholder review.
• Work closely with Credit Risk, Finance, Underwriting, Collections, Product, Data and Engineering teams to track model requirements and translate business needs into practical solutions, while complying with all mandatory policies and maintaining a strong internal control environment.

What you'll need

• At least 5 years' hands-on risk modelling experience
• Applying statistical modelling techniques such as logistic and linear regression, as well as machine learning models, to solve practical business problems
• Comfortable with large data sets, and data extraction and manipulation using Excel, SQL, Python and BI tools
• Proven track record with Python coding
• Comfortable using GenAI tools to increase coding productivity
• Good understanding of IFRS9, credit and lending concepts
• Ability to work independently and adapt quickly to changing priorities in a very dynamic environment
• Works well with stakeholders across the business, and collaboratively within the team
• Strong skills in writing technical documents as well as business-focused documents to get buy-in from various stakeholders

Nice to have

• Good understanding of IFRS9, credit and lending concepts preferably in commercial lending
• Experience of implementation of models into software applications

Details

• Location: Delhi
• Flexible and hybrid working available