Application Development Business Analyst

EXL

3 - 6 years

3 - 7 Lacs

gurugram

Posted:1 week ago| Platform:

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Skills Required

automation risk analytics risk modeling workflow data quality business continuity macros sql auditing python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Key Responsibilities

Analyze existing
Excel and VBA-based loss forecasting models
and document underlying business logic and assumptions
Translate Excel formulas, macros, and manual processes into
Python-based scripts and workflows
Develop automated pipelines for
data ingestion, transformation, and forecast generation
Perform
loss forecasting, back-testing, and sensitivity analysis
on consumer credit portfolios
Use
SQL
to extract, validate, and reconcile data from databases and data warehouses
Ensure Python outputs reconcile with legacy Excel forecasts and meet defined tolerance thresholds
Build reusable, modular, and well-documented Python code for ongoing production use
Support scenario analysis and stress testing through parameterized Python models
Collaborate with risk, finance, and business stakeholders to validate assumptions and outputs
Maintain version control, documentation, and audit trails for models and forecasts

Required Skills & Qualifications

3-6 years of experience in
banking analytics, loss forecasting, or credit risk modeling
Strong proficiency in
Python
(pandas, NumPy, basic modeling/statistical libraries)
Advanced
Excel
skills, including experience with complex formulas and macros (VBA)
Solid
SQL
skills for querying and validating large datasets
Hands-on experience with
loss forecasting methodologies
(roll rates, vintage analysis, PD/LGD, or loss rate forecasting)
Strong analytical skills with attention to detail and data quality

Preferred / Nice-to-Have Skills

Experience working in
banking, credit cards, unsecured lending, or BNPL portfolios
Familiarity with
automation frameworks, schedulers, or workflow tools
Experience validating or migrating legacy models to modern analytics platforms

Required Skills & Qualifications

2-4 years of experience in
banking analytics, loss forecasting, or credit risk modeling
Strong proficiency in
Python
(pandas, NumPy, basic modeling/statistical libraries)
Advanced
Excel
skills, including experience with complex formulas and macros (VBA)
Solid
SQL
skills for querying and validating large datasets
Hands-on experience with
loss forecasting methodologies
(roll rates, vintage analysis, PD/LGD, or loss rate forecasting)
Strong analytical skills with attention to detail and data quality

Key Responsibilities

Analyze existing
Excel and VBA-based loss forecasting models
and document underlying business logic and assumptions
Translate Excel formulas, macros, and manual processes into
Python-based scripts and workflows
Develop automated pipelines for
data ingestion, transformation, and forecast generation
Perform
loss forecasting, back-testing, and sensitivity analysis
on consumer credit portfolios
Use
SQL
to extract, validate, and reconcile data from databases and data warehouses
Ensure Python outputs reconcile with legacy Excel forecasts and meet defined tolerance thresholds
Build reusable, modular, and well-documented Python code for ongoing production use
Support scenario analysis and stress testing through parameterized Python models
Collaborate with risk, finance, and business stakeholders to validate assumptions and outputs
Maintain version control, documentation, and audit trails for models and forecasts

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