Full Time Fraud Data Scientist information
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$66.4K - $80.9K
6% of jobs
$80.9K - $95.3K
9% of jobs
$100K is the 25th percentile. Wages below this are outliers.
$95.3K - $109.8K
15% of jobs
The median wage is $119.4K / yr.
$109.8K - $124.2K
22% of jobs
$132.2K is the 75th percentile. Wages above this are outliers.
$124.2K - $138.7K
32% of jobs
$138.7K - $153.1K
3% of jobs
$153.1K - $167.6K
4% of jobs
$167.6K - $182K
1% of jobs
$182K - $196.5K
2% of jobs
How much do full time fraud data scientist jobs pay per year?
As of Aug 16, 2026, the average yearly pay for full time fraud data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.
A Full Time Fraud Data Scientist often works closely with teams such as engineering, product management, and fraud operations. Collaboration involves sharing insights from data analysis, discussing fraud patterns, and working together to design and implement detection algorithms. Regular cross-functional meetings are common, allowing data scientists to understand the needs of other teams and ensure that models are practical and aligned with business goals. This collaborative environment helps to rapidly identify emerging threats and continuously improve fraud prevention strategies.
To thrive as a Full Time Fraud Data Scientist, you need strong analytical skills, expertise in statistics and machine learning, and a relevant degree in fields like computer science, mathematics, or data science. Familiarity with programming languages such as Python or R, experience with big data platforms (e.g., Hadoop, Spark), and knowledge of fraud detection tools or frameworks are typically required. Exceptional problem-solving abilities, attention to detail, and effective communication skills help you interpret data and collaborate with cross-functional teams. These skills are crucial for identifying fraudulent activities accurately and efficiently, protecting organizations from financial losses and reputational damage.
A Full Time Fraud Data Scientist is responsible for analyzing large datasets to detect and prevent fraudulent activities within an organization. They use statistical models, machine learning algorithms, and data mining techniques to identify suspicious patterns and anomalies. Their work helps develop automated systems that flag or stop fraudulent transactions in real-time. Additionally, they collaborate with other teams such as cybersecurity, risk management, and compliance to ensure robust fraud detection and prevention strategies.
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