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Overnight Fraud Data Scientist Jobs (NOW HIRING)

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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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Overnight Fraud Data Scientist information

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$243.5K

How much do overnight fraud data scientist jobs pay per year?

As of Sep 5, 2026, the average yearly pay for overnight 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 does an overnight fraud data scientist do?

An Overnight Fraud Data Scientist is responsible for analyzing transaction data and monitoring for fraudulent activity during nighttime hours when fewer staff are present. They use statistical models, machine learning, and data analysis tools to detect unusual patterns that may indicate fraud, helping organizations minimize risk and financial losses. Their role often involves real-time monitoring, rapid response to alerts, and collaborating with other teams to improve detection systems. Overnight shifts are crucial as fraudulent activities may spike outside typical business hours, requiring constant vigilance.

What skills and qualifications are needed to be an overnight fraud data scientist?

To excel as an Overnight Fraud Data Scientist, you need a strong background in statistics, machine learning, data analysis, and a relevant degree in fields such as computer science or mathematics. Familiarity with programming languages like Python or R, experience using big data platforms (e.g., Hadoop, Spark), and knowledge of fraud detection systems are typically required. Excellent problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and collaborate across teams. These competencies are crucial for identifying fraudulent activity quickly and accurately during overnight hours to protect organizational assets and minimize risk.

How does an overnight fraud data scientist interact with other teams to detect and prevent fraud?

Overnight Fraud Data Scientists often work closely with fraud analysts, risk management teams, and IT professionals to monitor suspicious activity in real time. They are responsible for analyzing transaction data, developing detection models, and rapidly communicating findings to relevant stakeholders, even outside regular business hours. This collaboration ensures that fraud is identified and addressed promptly, minimizing potential losses for the organization. Being proactive and having strong communication skills are essential for effective teamwork in this fast-paced environment.

What is the difference between Overnight Fraud Data Scientist vs Fraud Analyst?

AspectOvernight Fraud Data ScientistFraud Analyst
CredentialsBachelor's/Master's in Data Science, Statistics, or related fieldBachelor's in Criminal Justice, Finance, or related field
Work EnvironmentData-driven, analytical, often remote or night shiftsCustomer service, investigation, on-site or remote during business hours
Industry UsageFinancial institutions, e-commerce, fintech companiesBanking, credit card companies, retail
Search/Comparison IntentUnderstanding technical data roles in fraud detectionOperational fraud investigation and customer support

The Overnight Fraud Data Scientist focuses on analyzing large datasets to develop models that detect fraud, often working overnight or remotely. In contrast, a Fraud Analyst typically investigates suspicious activity, reviews alerts, and interacts with customers during regular hours. Both roles are essential in fraud prevention but differ in technical expertise, work hours, and daily responsibilities.

What cities are hiring for Overnight Fraud Data Scientist jobs?

Cities with the most Overnight Fraud Data Scientist job openings:

What are the most commonly searched types of Fraud Data Scientist jobs?

The most popular types of Fraud Data Scientist jobs are:

What states have the most Overnight Fraud Data Scientist jobs?

States with the most job openings for Overnight Fraud Data Scientist jobs include:

Overnight Fraud Data Scientist jobs near you
Infographic showing various Overnight 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

Re-posted 9 days ago

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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