Fraud Data Analytics

Innodata Inc.; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Innodata Inc. in Hyderabad, India, seeks an experienced fraud risk investigator to join our Trust & Safety team. The role requires 5+ years of hands-on experience in fraud, abuse, risk, or related investigations and the ability to manage complex cases.

You will analyze signals across behavioral, transactional, and system data, write precise case documentation, and articulate evidence to support classifications. Strong SQL skills and independent, detail-oriented work are essential.

Qualifications

• 5+ years of hands-on experience in fraud, abuse, risk, trust & safety, financial crime, or a closely related investigation function.
• Strong experience handling complex investigations, escalations, or cases requiring significant analyst judgment.
• Demonstrated ability to investigate cases using multiple behavioral, transactional, account, or system signals.
• Advanced SQL proficiency, including complex queries, joins, window functions, and independent analysis of large datasets.
• Strong analytical reasoning and ability to distinguish meaningful signals from noise.
• Experience identifying fraud patterns, control gaps, detection gaps, false positives, and false negatives.
• Ability to clearly articulate why a case should be classified in a particular way and identify the evidence supporting the decision.
• Strong written communication and case-documentation skills.
• Ability to operate independently with limited step-by-step guidance.

Skills

Fraud domain knowledge

Investigation and case handling

Signal analysis

Independent work

Written communication

Evidence articulation

Tools

SQL

Job description

• 5+ years of hands-on experience in fraud, abuse, risk, trust & safety, financial crime, or a closely related investigation function.
• Strong experience handling complex investigations, escalations, or cases requiring significant analyst judgment.
• Demonstrated ability to investigate cases using multiple behavioral, transactional, account, or system signals.
• Advanced SQL proficiency, including complex queries, joins, window functions, and independent analysis of large datasets.
• Strong analytical reasoning and ability to distinguish meaningful signals from noise.
• Experience identifying fraud patterns, control gaps, detection gaps, false positives, and false negatives.
• Ability to clearly articulate why a case should be classified in a particular way and identify the evidence supporting the decision.
• Strong written communication and case-documentation skills.
• Ability to operate independently with limited step-by-step guidance.