Banking Analytics Professionals

NTT DATA, Inc.; Chennai District; On-site; INR 900,000 - 1,300,000; Full time

Job summary

NTT DATA, Inc. is seeking a data-driven analyst in Chennai to support AML/KYC governance through risk reporting and data mining. You will extract data from multiple banking systems, build repeatable reporting pipelines, and mine large datasets for suspicious patterns.

The role requires a strong background in data tools (SQL, Power BI) and programming (Python, R). Collaboration with compliance, IT, and relationship managers is key.

Qualifications

• Degree in Computer Science, Finance, Business, Mathematics or Statistics.
• SQL is essential for data extraction; Python/SAS/R for advanced risk modelling.
• Advanced Excel for tracking metrics and daily analysis.
• Power BI for dashboards; SharePoint and VBA for tooling.

Responsibilities

• Maintain reporting cadences for AML/KYC governance.
• Build and manage data pipelines from banking systems for risk reporting.
• Coordinate with relationship managers, compliance, and IT to resolve data quality issues.

Education

Bachelor's degree in Computer Science, Finance, Business, Mathematics, or Statistics

Tools

Power BI

SQL

Python

SAS

R

Excel

SharePoint

VBA Script

Job description

Job Description:

Core Responsibilities

• Risk Reporting & Monitoring: Maintain consistent reporting cadences for AML/KYC governance. This includes creating management information (MI) reports on risk exposure, trending, and remediation progress for senior leadership.
• Data Analysis & Mining: Extract and manage data from multiple banking systems to build repeatable reporting pipelines. Use statistical techniques to mine large datasets for suspicious patterns, delinquencies, or "red flags".
• Stakeholder Coordination: Liaise with relationship managers, compliance officers, and IT teams to resolve data quality issues and validate risk models.

Key Qualifications & Tech Stack

• Educational Background: Typically requires a degree in Computer Science, Finance, Business, Mathematics, or Statistics.
• Data Tools:
  • Visualization: Microsoft Power BI for automated dashboards or Web dashboards.
  • Database/Scripting: SQL (essential for data extraction), and sometimes Python or SAS/R for advanced risk modelling.
  • Spreadsheets: Advanced Microsoft Excel for tracking metrics and daily analysis.
  • Tools: SharePoint, Phyton, VBA Script