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Fraud Strategy Data Scientist

San Jose, CA · On-site

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve ...

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How much do fraud data scientist jobs pay per year?

As of Sep 6, 2026, the average yearly pay for fraud data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a fraud data scientist?

A Fraud Data Scientist analyzes transactional and behavioral data to detect, prevent, and mitigate fraudulent activities. They use machine learning models, statistical analysis, and anomaly detection techniques to identify suspicious patterns in financial, e-commerce, or other data-heavy industries. Their role involves working with large datasets, collaborating with fraud investigators, and continuously improving fraud detection systems to minimize financial losses and risks.

What are the typical daily responsibilities of a fraud data scientist?

A Fraud Data Scientist's day often involves analyzing large datasets to detect suspicious patterns, developing and validating machine learning models to predict fraudulent activity, and collaborating with other teams such as compliance and risk management. Additionally, they may respond to real-time fraud alerts, participate in meetings to refine detection strategies, and prepare reports for stakeholders. The role combines technical analysis with ongoing learning about emerging fraud trends, making every day dynamic and intellectually challenging. Teamwork and adaptability are essential, as you'll frequently coordinate with engineers and business leaders to continually enhance fraud prevention efforts.

What are the key skills and qualifications needed to thrive in the fraud data scientist position, and why are they important?

To thrive as a Fraud Data Scientist, you need strong analytical skills in statistics, machine learning, and data analysis, typically backed by a degree in data science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with SQL databases, and knowledge of fraud detection tools such as SAS, Hadoop, or relevant certifications like CFE are highly valued. Excellent problem-solving ability, communication skills, and the capacity to work collaboratively with cross-functional teams are important soft skills. These abilities are crucial for identifying and mitigating fraudulent activities while ensuring clear collaboration and actionable insights in a high-stakes financial environment.

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Fraud Data Scientist jobs near you
Infographic showing various Fraud Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Fraud Data & Technology Analyst

United Community Bank

Greenville, SC • On-site

$49.97 - $76.96/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Overview

The Fraud Data & Technology Analyst drives data-informed decision-making through analytics, reporting, technology support, and rule optimization. This role delivers actionable insights, evaluates fraud trends and program performance, and supports initiatives that strengthen detection, prevention, and mitigation capabilities. Working closely with the Fraud Data & Technology Lead and cross-functional partners, the analyst helps optimize fraud technologies, enhance controls, improve operational effectiveness, and strengthen customer protection.

This position is available in Greenville, SC and Blairsville, GA.

What You’ll Do
  • Reporting & Analytics
    • Build, automate, and maintain fraud KPIs, dashboards, and reports to measure program performance, loss drivers, mitigation outcomes, and emerging fraud trends.
    • Analyze fraud data and translate complex findings into actionable insights, recommendations, and strategic reporting for leadership, operations, and frontline teams.
    • Conduct performance assessments, cost-benefit analyses, business case development, and industry research to support fraud strategy, risk identification, and continuous improvement initiatives.
  • Fraud Technology Support
    • Support the administration, maintenance, optimization, and performance of fraud-related applications, platforms, tools, and system enhancements.
    • Coordinate and participate in testing, validation, implementation, troubleshooting, issue resolution, and performance monitoring to ensure technology effectiveness and operational reliability.
    • Partner with internal technology teams, business stakeholders, and vendors to support fraud technology initiatives while documenting business processes, system functionality, and operational workflows for governance and knowledge sharing.
  • Rules & Model Management
    • Tune, calibrate, and optimize fraud detection rules, models, and decisioning strategies to improve detection effectiveness while balancing operational efficiency and customer experience.
    • Analyze rule and model performance through testing, alert reviews, and performance metrics, recommending enhancements to fraud monitoring strategies and detection controls.
  • Data Management
  • Ensure the accuracy, integrity, reliability, and quality of data used in fraud reporting, analysis, and decision-making.
  • Support data governance initiatives through documentation, maintenance of data dictionaries and reporting methodologies, quality validation, issue identification, and adherence to reporting standards.
  • Cross-Functional Partnership
    • Collaborate with stakeholders to identify opportunities for process improvements, automation, and enhanced fraud controls.
    • Partner with Fraud Operations, Risk, Compliance, IT, and business teams to support fraud mitigation efforts.
    • Provide analytical support and subject matter expertise for fraud-related initiatives.
Requirements For Success
  • Bachelor's degree or higher preferred
  • 3+ years of experience in fraud analytics, fraud technology or operations, risk management, or a related field.
  • Required Skills:
    • Hands-on experience with fraud and/or banking platforms.
    • Experience with data visualization and reporting tools (e.g., Tableau, Power BI, etc.).
    • Experience querying and analyzing large datasets using SQL or similar data analysis tools.
    • Knowledge of fraud typologies across payments, digital identity, account takeover, and application fraud.
    • Strong analytical, problem-solving, and communication skills.
    • Demonstrated ability to collaborate effectively with cross-functional teams.
  • Preferred Skills:
    • Experience with machine learning concepts or partnering with data science teams.
    • Experience creating or maintaining process maps for technical or operational processes
    • Familiarity with APIs, system integrations, or cloud-based data environments.
    • Ability to present complex data insights in a clear and concise manner to both technical and non-technical audiences.
Conditions of Employment
  • Must be able to pass a criminal background & credit check
  • This is a full-time, non-remote position that requires schedule flexibility to work evenings and weekends as needed.
  • Up to 10% of travel may be required.

FLSA Status:Exempt

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state, or local protected class.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Pay Range

USD $49,972.00 - USD $76,958.00 /Yr.

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