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Fraud Analytics Jobs (NOW HIRING)

Nuvative Inc

Fraud & Analytics Manager

Wichita, KS · On-site

Analytics JOB TITLE : Manager of Fraud Analytics REPORTS TO : VP of Credit Risk & Analytics WHO WE ARE: Nuvative is a parent company that is helping businesses meet their goals through innovative ...

Nuvative Inc

Fraud & Analytics Manager

Wichita, KS · On-site

Analytics JOB TITLE : Manager of Fraud Analytics REPORTS TO : VP of Credit Risk & Analytics WHO WE ARE: Nuvative is a parent company that is helping businesses meet their goals through innovative ...

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 ...

Avant

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 ...

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 ...

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How much do fraud analytics jobs pay per hour?

As of Aug 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.

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.

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 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.

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.

How do I become a fraud analyst?

To become a fraud analyst, typically a bachelor's degree in finance, accounting, or a related field is required. Relevant skills include data analysis, knowledge of fraud detection tools, and familiarity with databases and reporting software; certifications like Certified Fraud Examiner (CFE) can enhance prospects. Gaining experience through internships or entry-level roles in finance or security is also beneficial.

How much does a fraud analyst get paid?

A fraud analyst's salary typically ranges from $50,000 to $80,000 annually, depending on experience, location, and industry. Entry-level positions may start lower, while experienced analysts with certifications or specialized skills can earn higher salaries. Many roles also include benefits such as bonuses and professional development opportunities.

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.

What does a fraud analytics do?

A fraud analyst uses data analysis techniques to detect and prevent fraudulent activities within financial transactions or business operations. They analyze large datasets, identify patterns of suspicious behavior, and implement strategies to reduce fraud risk, often using tools like SQL, Excel, or specialized fraud detection software. Strong analytical skills and knowledge of fraud schemes are essential for this role.
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Fraud Analytics jobs near you
Infographic showing various Fraud Analytics job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 93% Full Time, 3% Part Time, and 3% Contract. Highlights an 78% Physical, 7% Hybrid, and 15% Remote job distribution, with an average salary of $63,822 per year, or $30.7 per hour.

Transaction Fraud Analytics (Senior Fraud Risk Analyst)

ATLANTICUS

Atlanta, GA • Hybrid

Full-time

Re-posted 12 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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