Data Scientist Fraud & AML Analytics

Hiring Squad; Mumbai; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Hiring Squad is seeking an experienced Analytics professional to join its fraud and AML investigations in Mumbai. You will analyse large transactional datasets from banking, customer, vendor and financial sources to detect indicators of fraud.

The role requires 5-7 years of experience, proficiency in Python, SQL, Excel and Power Query, and the ability to present clear, source-referenced analysis with dashboards and investigation outputs.

Qualifications

• 5-7 years of experience in fraud analytics or AML
• Experience analysing large transactional and financial datasets
• Preferred: CAMS, CFE, CFCS or relevant Data Analytics certification

Responsibilities

• Analyse large transaction, banking, customer, vendor and financial datasets for fraud and AML indicators.
• Identify suspicious patterns, anomalies, mule accounts, unusual fund movements and related-party linkages.
• Perform fund-flow, money-trail and transaction chronology analysis.
• Analyse bank statements, invoices, vendor masters, payment records and approval trails.
• Use Python, SQL, Excel and Power Query for data cleaning, reconciliation and analytics.
• Develop dashboards, exception reports, relationship maps and investigation outputs.
• Support AML, fraud and forensic investigations with evidence-backed analytical findings.
• Identify data gaps, inconsistencies and areas requiring further investigation.
• Maintain clear, source-referenced working papers and methodology.
• Use AI tools for investigation analytics and triage, with proper human validation.

Skills

Forensic / AML / Fraud Analytics

Transaction & Financial Crime Analysis

Python, SQL, Excel, Power Query

Fund Flow & Money Trail Analysis

Anomaly / Pattern Detection

BFSI / Banking Data

AI-assisted Investigation Analytics

Tools

Python, SQL, Excel, Power Query

Job description

Experience: 5-7 years

Key Responsibilities

• Analyse large transaction, banking, customer, vendor and financial datasets for fraud and AML indicators.
• Identify suspicious patterns, anomalies, mule accounts, unusual fund movements and related-party linkages.
• Perform fund-flow, money-trail and transaction chronology analysis.
• Analyse bank statements, invoices, vendor masters, payment records and approval trails.
• Use Python, SQL, Excel and Power Query for data cleaning, reconciliation and analytics.
• Develop dashboards, exception reports, relationship maps and investigation outputs.
• Support AML, fraud and forensic investigations with evidence-backed analytical findings.
• Identify data gaps, inconsistencies and areas requiring further investigation.
• Maintain clear, source-referenced working papers and methodology.
• Use AI tools for investigation analytics and triage, with proper human validation.

Key Skills

• Forensic / AML / Fraud Analytics
• Transaction & Financial Crime Analysis
• Python, SQL, Excel, Power Query
• Fund Flow & Money Trail Analysis
• Anomaly / Pattern Detection
• BFSI / Banking Data
• AI-assisted Investigation Analytics

Preferred: CAMS, CFE, CFCS or relevant Data Analytics certification.