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Banking Loss Forecasting Report Automation Specialist

Bangalore, Chennai, Hyderabad
Job Description
Key Responsibilities  
  • Develop, implement, and maintain automated pipelines for loss forecasting reports using advanced data and  reporting tools (e.g., Python, SQL, Tableau).  
  • Automate end-to-end processes for Expected Credit Loss (ECL), Probability of Default (PD), Loss Given  Default (LGD), Exposure at Default (EAD), and Transition Matrix–based frameworks.
  • Understanding of credit risk modeling (CECL, IFRS 9, stress testing, and Basel reporting).
  • Collaborate with risk, finance, and data engineering teams to gather requirements and ensure automation  aligns with business and regulatory needs. 
  • Design and optimize data extraction, transformation, and loading (ETL) processes to source data from  multiple banking systems.
  • Build validation, reconciliation, and exception-handling routines to ensure reporting accuracy and integrity.
  • Create dashboards and self-service reporting tools for senior management and regulatory stakeholders. 
  • Continuously improve automation frameworks, ensuring scalability and adaptability to regulatory changes. 
  • Support ad-hoc analysis, model integration, and performance monitoring of forecasting methodologies.

Job Requirement
Qualifications & Skills
  • 3–7 years of experience in banking risk management, finance, or data analytics, with exposure to credit risk  and loss forecasting.
  • Prior experience with report automation in CECL, IFRS 9, Basel, or stress testing frameworks strongly  preferred.
  • Strong proficiency in understanding of vintage models, roll rate models, and time series based risk models.
  • Ability to translate credit policy and macro environment inputs into portfolio impacts, including DQ, Low FICO  concentration, Exposure, Credit and Fraud Losses. Good understanding of credit card maturation,  vintage/cohort analysis.
  • Bachelor’s or Master’s in Finance, Statistics, Data Science, Computer Science, or a related field
Good to have  

  • Strong programming skills in Python, SQL, pyspark for data manipulation and automation. 
  • Experience with ETL tools, workflow automation (Airflow etc.), and data visualization (Tableau). Email  automation is an added bonus.
  • Knowledge of cloud platforms (AWS, Databricks) and version control (Git) is a plus. 
  • Familiarity with statistical/machine learning models for loss forecasting desirable.