Location : Bangalore
Experience Required : 5 -12 Years (Minimum 4 years of relevant experience)
Department : Transformation / Data Vetting
Mandatory Skills : Advanced Python + Corporate Loan Lifecycle + Credit Risk / Lending Knowledge
About the Role :
We are seeking an experienced professional to join our team as an Assistant Vice President - Data Vetting Specialist. In this role, you will lead the meticulous vetting of data for diverse corporate loan structures, ensure high data hygiene for regulatory compliance, and bridge the gap between financial risk models and core data infrastructure.
Key Responsibilities :
- - Data Vetting & Validation : Perform deep data vetting for corporate loan structures (bilateral, syndicated, revolving credit) and validate critical lifecycle events like maturity extensions and limit modifications against legal docs.
- - Risk & Compliance Audit: Audit data triggers for covenant compliance, potential breaches, or defaults.
- - Restructuring & Recovery: Oversee data integrity for restructured loans and support Default and Recovery teams by tracking collateral valuations and write-off data.
- - Reconciliation: Reconcile complex loan data across front-office booking systems, back-office servicing platforms, and Credit Risk models (ECL, PD/LGD).
- - Data Automation: Investigate data discrepancies between General Ledger (G/L) records and sub-ledgers using automated data workflows.
Required Skills & Qualifications :
- 1. Domain & Technical Expertise (Mandatory)
- - Advanced Python (Must-Have): Strong, hands‑on experience in using Python for data manipulation, cleaning, and automation.
- - Credit & Lending Knowledge: Deep understanding of corporate loan specifications (floating/fixed rates, amortization, collateral types).
- - Credit Risk Frameworks: Strong familiarity with risk parameters (EAD, LGD) and financial accounting principles for loan loss provisioning (IFRS 9).
- - Loan Systems & Processes: Experience with Insolvency/Debt Restructuring and hands‑on experience with Loan Servicing Systems (e.g., FIS, Misys/Finastra, or similar core banking platforms).
- 2. Data & Analytics :
- - Proficiency in SQL and advanced Excel (VBA/Power Query).
- - Experience with BI tools like Power BI or Tableau to visualize portfolio trends.
- 3. Education & Experience :
- - Experience : 5 to 12 years of overall experience,with at least 4 years specifically in data vetting, credit analysis, or loan operations within a commercial/investment bank.
- - Education: Bachelors or Masters degree in Finance, Accounting, or Data Science.
- - Preferred Certifications: CFA or ACCA will be highly preferred. .