Automation (India)

Job Description: We are seeking a Risk Analytics / Loss Forecasting Analyst with strong Python, Excel, and SQL skills to support the automation and modernization of consumer credit loss forecasting processes . The role focuses on transitioning existing Excel and Excel macrobased forecasting models into scalable, auditable SQL and Python scriptbased workflows , while ensuring accuracy, governance, and business continuity. 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 - 24 years of experience in banking analytics, loss forecasting, or credit risk modeling - Solid 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 Responsibilities: 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 Qualifications: Required Skills & Qualifications - 24 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 .