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Full Time Fraud Data Scientist Jobs (NOW HIRING)

Suncoast Credit Union

Senior Fraud Data Analyst

Tampa, FL · Remote

$75K - $117K/yr

Remote (candidate must reside in FL) Position Type: Full Time The Senior Fraud Analyst actively ... The senior analyst leverages state-of-the-art industry data science tools to synthesize and analyze ...

Truist

Data Scientist I - Card Fraud

Atlanta, GA · On-site

... Data Scientist I to support card fraud and token provisioning initiatives, with a focus on digital ... by full-time or part-time status) during their first year of employment, along with 10 sick days ...

Truist

Data Scientist I - Card Fraud

Atlanta, GA · On-site

... Data Scientist I to support card fraud and token provisioning initiatives, with a focus on digital ... by full-time or part-time status) during their first year of employment, along with 10 sick days ...

BILL

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 ...

Rain

Data Scientist - Fraud Risk

New York, NY · On-site +1

$50K/yr

Background in identity risk, AML, payments fraud, or compliance analytics * Fluency in AI-assisted data analysis / data science tooling Things that enable a fulfilling, healthy, and happy experience ...

Booz Allen Hamilton

Data Scientist

Doral, FL · On-site

$112K - $257K/yr

Across private and public sectors, from fraud detection to cancer research, to national ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist

Doral, FL · On-site

$112K - $257K/yr

Across private and public sectors, from fraud detection to cancer research, to national ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist

Dayton, OH · On-site

$77K - $176K/yr

Across private and public sectors-from fraud detection to cancer research to national intelligence ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton

Data Scientist

Dayton, OH · On-site

$77K - $176K/yr

Across private and public sectors-from fraud detection to cancer research to national intelligence ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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All JobsFraud Data Scientist JobsFull Time Fraud Data Scientist Jobs

Full Time Fraud Data Scientist information

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$122.7K

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How much do full time fraud data scientist jobs pay per year?

As of Aug 17, 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.

How does a full time fraud data scientist typically collaborate with other departments to develop effective fraud detection solutions?

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.

What are the key skills and qualifications needed to thrive as a full time fraud data scientist?

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.

What does a full time fraud data scientist do?

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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Full Time Fraud Data Scientist jobs near you
Infographic showing various Full Time Fraud Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Staff Data Scientist - Fraud & Risk

Socure

Manhattan, NY • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Socure is building the identity trust infrastructure for the digital economy, focusing on verifying identities and preventing fraud. The Staff Data Scientist will design and optimize advanced machine learning models for fraud detection and risk management, while also mentoring peers and driving project success.
Responsibilities:
• Design, develop, and implement advanced deep learning models, including transformers, CNNs/RNNs, and graph learning algorithms, to address complex fraud and risk challenges.
• Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
• Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments.
• Take ownership of project outcomes, data quality, and delivery timelines; proactively escalate issues and work collaboratively to resolve challenges.
• Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning.
• Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions.
• Conduct in-depth research to explore new data sources and develop novel algorithms that advance the state of the art in fraud detection.
• Present findings and recommendations to technical and executive stakeholders with clarity and influence.
• Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
• Model Socure’s embedded leadership competencies: continuous learning, effective communication, accountability, team development, decision making, and managing change.
Qualifications:
Required:
• Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field; or equivalent professional experience.
• 8+ years of experience in data science, machine learning, or related fields, ideally in a high-growth tech or fintech environment.
• Experience in fraud prevention, risk modeling, or identity verification.
• Years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs/RNNs, and graph learning).
• Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.
• Strong proficiency in Python, SQL, and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Deep understanding of machine learning algorithms, model evaluation techniques, and data pipeline development.
• Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions.
• Excellent communication skills with the ability to translate complex data problems into actionable business insights for both technical and non-technical audiences.
• Commitment to continuous learning, professional integrity, and high standards of business ethics.
Preferred:
• Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
• Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus
Company:
Socure is a predictive analytics platform for digital identity verification of consumers. Founded in 2012, the company is headquartered in Incline Village, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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