Assistant Vice President - Data Vetting - Corporate Banking & Risk Vertical

Assistant Vice President Data Vetting Specialist (Corporate Banking & Risk)

CRITICAL NOTE FOR APPLICANTS :

This is a Corporate Banking & Advanced Data Automation role. Candidates with experience only in Retail Lending, Personal Loans, or Credit Cards will NOT be considered. Hands-on experience in Corporate Loans & Python/SQL is mandatory.

About the Role :

We are seeking an experienced, tech-savvy Finance/Risk professional to join our team in the role of Assistant Vice President - Data Vetting Specialist. In this role, you will bridge the gap between heavy financial data structures and automation. You will lead the meticulous vetting of data for complex Corporate Loan structures while leveraging Advanced Python to build automated data pipelines and reconciliation workflows.

Key Responsibilities :

- Corporate Loan Vetting : Perform meticulous vetting of data for diverse corporate loan structures, including Bilateral, Syndicated, and Revolving Credit facilities.

- Lifecycle Validation : Validate critical lifecycle events (maturity extensions, limit modifications) ensuring strict alignment with legal documentation.

- Risk & Compliance Audit : Audit data triggers for covenant compliance, potential breaches, or defaults.

- Reconciliation & Modeling : Reconcile loan data across front-office booking systems, back-office platforms, and Credit Risk models (ECL, PD/LGD models under IFRS 9 framework).

- Data Automation : Investigate and resolve data discrepancies between General Ledger (G/L) records and underlying loan sub-ledgers using Python-driven automation.

Required Skills & Qualifications :

1. Domain Expertise (Mandatory) :

- Deep knowledge of Corporate Loan Lifecycle & Specifications (floating/fixed rates, amortization schedules, collateral types).

- Solid understanding of Credit Risk parameters (EAD, LGD) and Finance/Accounting principles related to loan loss provisioning (IFRS 9).

- Familiarity with Insolvency and Debt Restructuring processes.

- Hands-on experience with Loan Servicing Systems (e.g., FIS, Misys/Finastra, or similar core wholesale banking platforms).

2. Technical & Analytical Skills :

- Advanced Python (Must-Have) : Proven experience in writing clean, scalable Python scripts for large-scale data manipulation, data vetting, and automation.

- Proficiency in SQL and Excel (VBA/Power Query).

- Experience with BI tools (Power BI or Tableau) to visualize data health and portfolio trends.

3. Experience & Education :

- Experience : 5 to 12 years overall, with at least 4 years of solid experience in data vetting, credit analysis, or corporate loan operations within a commercial/investment bank.

- Education : Bachelors or Masters degree in Finance, Accounting, or Data Science. Professional certifications like CFA or ACCA are highly desirable.