Remote Fraud & Risk Analyst (Contract)

TEK Systems; Austin (TX); Remote; USD 23,000 - 32,000; Part time

Job summary

TEKsystems is seeking a Contract Fraud Analyst in Austin, TX to master our adversarial payments ecosystem and stay ahead of fraud trends. You will analyze large datasets to uncover meaningful signals and use in-house tools to label signals, images, and payments according to protocols.

You will collaborate across teams to improve fraud detection capabilities, handle time-sensitive escalations, and help refine labeling interfaces and processes while leveraging Excel and Google Suite for reporting

Qualifications

• BS or equivalent in a related field such as CS, cybersecurity, math, or business.
• 3+ years in online fraud investigations, trust & safety, and/or cybersecurity.
• Experience in data review and ML labeling.
• Excel data manipulation with ability to interpret charts and visuals.

Responsibilities

• Become an expert in the adversarial ecosystem for our payment products.
• Analyze large datasets to identify signals correlating with fraud.
• Label images, signals, and payments using in-house tools.
• Make informed decisions on difficult cases and improve review protocols.
• Identify new fraud trends and collaborate to enhance detection capabilities.
• Partner with teammates to improve labeling interface processes.

Skills

Fraud investigations

Data analysis

Excel data manipulation

ML labeling

Time-sensitive escalation handling

Education

Bachelor's degree or equivalent in related field

Job description

TEKsystems is seeking a Contract Fraud Analyst in Austin, TX to master our adversarial payments ecosystem and stay ahead of fraud trends. You will analyze large datasets to uncover meaningful signals and use in-house tools to label signals, images, and payments according to protocols.

You will collaborate across teams to improve fraud detection capabilities, handle time-sensitive escalations, and help refine labeling interfaces and processes while leveraging Excel and Google Suite for reporting