Senior Analyst, Lending Models

Allica Bank

. Design, build, implement and continuously refine credit risk models, including IFRS9 impairment models and statistical and machine learning models for automated lending decisions .

Posted 10/22/2026full-timeDelhi • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing credit risk models, including IFRS9 impairment models and machine learning techniques, while effectively collaborating with cross-functional teams to translate business needs into actionable solutions.

Highest-signal resume keywords

Credit Risk ModellingPython CodingStatistical Modelling TechniquesMachine Learning ModelsIFRS9 Understanding

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Hard Skills

Risk ModellingStatistical ModellingMachine LearningData ExtractionData ManipulationFeature EngineeringModel ValidationModel CalibrationAd-Hoc AnalysisPerformance Monitoring

Soft Skills

CollaborationAdaptabilityTechnical Writing

Tools & Technologies

PythonExcelSQLBI ToolsGenAI Tools

Industry Keywords

Credit RiskLending ConceptsCommercial LendingGovernanceIndependent Review

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design, build, implement and continuously refine credit risk models, including IFRS9 impairment models and statistical and machine learning models for automated lending decisions
Develop and deploy models in Python across the full model lifecycle
Prepare data, perform feature engineering, fit and validate models, implement models and assess ongoing performance
Perform ad-hoc analysis to optimise credit policy rules and decisioning flows
Use rule-firing, decision and outcome data to identify redundant, overlapping or mis-calibrated rules
Produce regular monitoring of population stability, discriminatory power, calibration, segment and vintage performance, decision rates and alignment with underwriting outcomes
Recalibrate or redevelop models based on portfolio experience, predicted versus actual outcomes, drift and mis-calibration
Lead root-cause investigations into model, rule or decisioning-flow underperformance
Build controlled, reproducible modelling processes and improve data, tooling and infrastructure
Document models, rules, assumptions, limitations and changes to support governance, independent review and validation
Collaborate with Credit Risk, Finance, Underwriting, Collections, Product, Data and Engineering teams
Translate business needs into practical solutions and work with third-party suppliers where required

Requirements

What you’ll need

At least 5 years’ hands-on risk modelling experience
Experience applying statistical modelling techniques such as logistic and linear regression
Experience applying machine learning models to practical business problems
Comfortable working with large data sets
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, preferably in commercial lending
Ability to work independently and adapt quickly to changing priorities
Ability to work collaboratively with stakeholders across the business and within the team
Strong technical and business-focused writing skills
Experience implementing models into software applications is highly desirable

Benefits

Comp & perks

Full onboarding support and continued development opportunities
Options for flexible working
Regular social activities
Pension contributions
Discretionary bonus scheme
Private health cover
Life assurance
Family friendly policies including enhanced Maternity & Paternity leave
Flexible and hybrid working