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Fraud Analytics Jobs (NOW HIRING)

ALOIS LLC

Sr Fraud Analyst

San Jose, CA · On-site

$140K - $165K/yr

Senior - Payments & Fraud Analytics Employment: Full-Time Location: San Jose, CA (Hybrid) | Full-Time Industry: Fintech For one of our Fortune client we are hiring for a high-impact Payments & Fraud ...

Aquent

Fraud Strategy & Model Risk Analytics

Irving, TX · On-site

$65 - $70/hr

Jul 20, 2026 Fraud Strategy & Model Risk Analytics Manager, Fraud Analytics & Governance Duration: 12 months, likely extension Pay: $65 - $67 / hourly as W2 Candidates need to work 3 days onsite each ...

Avant

Sr Associate, Fraud Analytics

Chicago, IL

$100K - $130K/yr

Avant is looking for knowledgeable fraud professionals to join our Fraud Analytics team in Chicago. This position is critical in utilizing data to identify fraud trends, developing and deploying ...

Credit One Bank

Fraud Analytics Manager

Las Vegas, NV · On-site

Position Summary Credit One Bank is seeking a Fraud Analytics Manager to lead vendor strategy, drive operational performance, and advance an AI-enabled fraud operations model. This leader will be ...

Avant LLC

Sr Associate, Fraud Analytics

Chicago, IL · On-site

$100K - $130K/yr

Avant is looking for knowledgeable fraud professionals to join our Fraud Analytics team in Chicago. This position is critical in utilizing data to identify fraud trends, developing and deploying ...

OceanFirst Bank

Fraud Analyst Manager

Toms River, NJ · On-site

Manages and conducts account/transaction monitoring utilizing appropriate software, applications, and manual review where necessary to perform fraud analytics. Initiates and manages appropriate ...

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Fraud Analytics information

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How much do fraud analytics jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for fraud analytics in the United States is $30.68, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $33.89 per hour, depending on experience, location, and employer.

How does a Fraud Analytics professional typically collaborate with other departments within an organization?

Fraud Analytics professionals frequently work cross-functionally, partnering with teams such as IT, compliance, risk management, and customer service. They analyze data to identify suspicious activities and then communicate findings to relevant stakeholders, often participating in investigations or recommending process improvements. Effective collaboration ensures that fraud detection strategies stay up-to-date and align with broader organizational goals, making strong communication skills and teamwork essential for success in this role.

What does a fraud analyst do?

A fraud analyst investigates and detects fraudulent activities by analyzing transaction data, patterns, and behaviors to identify potential scams or security breaches. They use tools like data analysis software and may review alerts from fraud detection systems to prevent financial losses and ensure compliance. Strong analytical skills and knowledge of fraud prevention techniques are essential for this role.

What is the difference between Fraud Analytics vs Fraud Prevention Specialist?

AspectFraud AnalyticsFraud Prevention Specialist
Primary FocusAnalyzing data to detect and predict fraudulent activitiesImplementing strategies and actions to prevent fraud
Skills & CertificationsData analysis, statistical tools, SQL, certifications like Certified Fraud Examiner (CFE)Customer service, risk management, fraud detection techniques, certifications like CFE
Work EnvironmentData analysis teams, financial institutions, tech companiesCustomer support centers, financial institutions, retail
GoalsIdentify patterns, develop models, improve detection accuracyReduce fraud incidents, enhance prevention measures

While both roles aim to combat fraud, Fraud Analytics focuses on analyzing data to identify and predict fraudulent activities, whereas Fraud Prevention Specialists implement measures to prevent fraud from occurring. Both roles often collaborate but serve different functions within fraud management strategies.

Will the fraud analyst be replaced by AI?

Fraud analysts play a critical role in detecting complex and evolving fraudulent activities that AI alone cannot fully address. While AI tools assist in automating routine tasks and analyzing large data sets, human judgment, critical thinking, and expertise remain essential in fraud prevention and investigation. Therefore, fraud analysts are likely to work alongside AI rather than be fully replaced by it.

What are the key skills and qualifications needed to thrive as a Fraud Analytics professional, and why are they important?

To thrive in Fraud Analytics, you need strong analytical abilities, proficiency in statistics, and experience with data analysis, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with data mining tools, SQL, Python, machine learning platforms, and certifications like Certified Fraud Examiner (CFE) are typically required. Attention to detail, critical thinking, and effective communication are essential soft skills for interpreting data patterns and presenting findings to stakeholders. These skills are crucial for detecting fraudulent activities, minimizing financial risks, and supporting organizational integrity.

How much does a fraud analyst earn?

The average salary for a fraud analyst typically ranges from $50,000 to $80,000 annually, depending on experience, location, and industry. Entry-level roles may start lower, while experienced analysts with certifications and advanced skills can earn higher salaries. Many fraud analysts also receive benefits such as bonuses and health insurance.

What is fraud analytics?

Fraud analytics is the process of using data analysis, statistical methods, and machine learning techniques to detect, prevent, and investigate fraudulent activities within an organization. Professionals in this field analyze large sets of transactional and behavioral data to identify patterns and anomalies that may indicate fraud. Fraud analytics is commonly used in industries such as banking, insurance, retail, and e-commerce to minimize financial losses and protect customers. The role often involves working with specialized software and collaborating with other teams to implement effective anti-fraud strategies.

Is fraud analysis a good career?

Fraud analysis is a growing field within risk management that involves detecting and preventing fraudulent activities using data analysis and investigative skills. It offers opportunities for advancement, requires knowledge of analytics tools, and often involves working in financial or e-commerce environments. The role can be stable and rewarding for those interested in security and data-driven decision making.
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Fraud Analytics jobs near you
Transaction Fraud Analytics (Senior Fraud Risk Analyst)

Transaction Fraud Analytics (Senior Fraud Risk Analyst)

ATLANTICUS

Atlanta, GA • Hybrid

Other

Posted 11 days ago

Job description

Job Description 

  • Title: Senior Analyst/Associate Transaction Fraud Analytics (Senior Fraud Risk Analyst)  
  • Location: Atlanta, GA (Hybrid)
  • Department: Risk Management/Fraud Prevention 

Responsibilities: 

  • Develop and implement fraud detection models using advanced analytics and machine learning techniques. 
  • Monitor real-time transaction data to identify and flag potentially fraudulent activities. 
  • Conduct root cause analysis of fraud incidents and recommend preventive measures. 
  • Collaborate with cross-functional teams, including IT, Information Security, and Customer Service, to enhance fraud management processes. 
  • Design and maintain dashboards and reports for fraud trends, KPIs, and risk assessments. 
  • Ensure compliance with regulatory requirements and industry standards related to fraud prevention. 
  • Stay updated on emerging fraud trends, tools, and technologies to strengthen detection capabilities. 

Qualifications: 

  • Bachelor’s or master’s degree in data science, Statistics, Finance, or a related field. 
  • 5+ years of experience in fraud analytics, data analysis withat least 3 being in transaction fraud, preferable credit cards. 
  • Should have experience in working on Fiserv related systems. 
  • Proficiency in data analytics tools such as SQL, Python, R, or SAS. 
  • Experience with transaction monitoring systems and fraud detection platforms. 
  • Strong understanding of payment systems, credit card processing, and e-commerce fraud schemes. 
  • Excellent problem-solving, analytical, and communication skills. 
  •  Needs experience with Advance Defense Edge

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