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Data Scientist Fraud Detection Jobs (NOW HIRING)

Democrance

NY · On-site

$120 - $180/hr

About this role: We're looking for a Data Scientist to sit at the heart of how we fight fraud -- building the models, experiments, and detection systems that protect millions of customers and ...

New

Unchain Data

Senior Data Scientist, Fraud

Menlo Park, CA · On-site

$187 - $220/hr

Design and deploy fraud detection models to protect Robinhood users and assets in real time ... data science or applied ML, with a focus on fraud detection or risk mitigation * Advanced ...

New

Moniepoint Group

NY · On-site

$120 - $180/hr

About this role: We're looking for a Data Scientist to sit at the heart of how we fight fraud -- building the models, experiments, and detection systems that protect millions of customers and ...

New

Equifax, Inc.

Senior Data Scientist - Fraud

Alpharetta, GA · On-site

$140 - $190/hr

Develop and productionize innovative GenAI and LLM-driven solutions for complex fraud detection ... Serve as a technical leader and mentor for junior data scientists and analysts, conducting code ...

Gemini

Senior Fraud Data Scientist

New York, NY · On-site +1

Senior Fraud Data Scientist As a Senior Fraud Data Scientist, you will play a critical role in ... This role requires strong experience with fraud detection systems, risk management methodologies ...

Sierra Ventures

Senior Fraud Data Scientist

Miami, FL · On-site

$116.25 - $155/hr

Senior Fraud Data Scientist As a Senior Fraud Data Scientist, you will play a critical role in ... This role requires strong experience with fraud detection systems, risk management methodologies ...

New

Gemini

Senior Fraud Data Scientist

New York, NY

Senior Fraud Data Scientist As a Senior Fraud Data Scientist, you will play a critical role in ... This role requires strong experience with fraud detection systems, risk management methodologies ...

Rain

Data Scientist - Fraud Risk

New York, NY · On-site +1

$50K/yr

... up fraud detection and response, and creating risk rules and strategies empowered with ML models ... Fluency in AI-assisted data analysis / data science tooling Things that enable a fulfilling ...

P2P

Data Scientist - Fraud Risk

Manhattan, NY · On-site

$120 - $190/hr

... up fraud detection and response, and creating risk rules and strategies empowered with ML models ... Fluency in AI‑assisted data analysis / data science tooling Things that enable a fulfilling ...

New

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All JobsData Scientist Fraud Detection Jobs

Data Scientist Fraud Detection information

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$37.5K

$122.7K

$196.5K

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

As of Aug 8, 2026, the average yearly pay for data scientist fraud detection 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.

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

To thrive as a Data Scientist in Fraud Detection, you need a strong background in statistics, machine learning, and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with big data tools (e.g., Hadoop, Spark), and knowledge of fraud detection platforms are essential. Strong problem-solving abilities, attention to detail, and effective communication skills set candidates apart in this field. These skills and qualities are crucial for identifying fraudulent activities quickly and accurately, minimizing financial losses, and supporting organizational security.

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

AspectData Scientist Fraud DetectionData Analyst Fraud Detection
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL
Work EnvironmentDeveloping models, advanced analytics, machine learning tasksData cleaning, reporting, basic analysis
Employer & Industry UsageFinancial institutions, e-commerce, insurance

Data Scientist Fraud Detection focuses on building predictive models and applying machine learning techniques to identify fraud patterns. Data Analysts Fraud Detection primarily perform data cleaning, reporting, and basic analysis to support fraud detection efforts. While both roles work in similar industries, Data Scientists handle more complex modeling, whereas Data Analysts focus on data interpretation and reporting.

How does a data scientist in fraud detection typically collaborate with other teams to develop effective solutions?

As a Data Scientist in Fraud Detection, you will regularly collaborate with cross-functional teams such as fraud analysts, software engineers, and product managers. Working closely with fraud analysts helps you understand emerging fraud patterns, while partnering with engineers ensures your models are effectively integrated into real-time systems. You may also coordinate with compliance and legal teams to ensure solutions meet regulatory requirements. This collaborative approach not only improves the accuracy and impact of fraud detection models but also fosters a dynamic, supportive work environment.

What does a data scientist in fraud detection do?

A Data Scientist in Fraud Detection analyzes large datasets to identify patterns and anomalies that could indicate fraudulent activities. They use machine learning algorithms, statistical models, and data mining techniques to detect and prevent fraud in areas like banking, insurance, and e-commerce. Their work helps organizations proactively combat fraud by developing predictive models and automated systems that flag suspicious transactions. Additionally, they often collaborate with other departments to refine detection strategies and ensure compliance with regulations.
More about Data Scientist Fraud Detection jobs
What cities are hiring for Data Scientist Fraud Detection jobs? Cities with the most Data Scientist Fraud Detection job openings:
What states have the most Data Scientist Fraud Detection jobs? States with the most job openings for Data Scientist Fraud Detection jobs include:
What job categories do people searching Data Scientist Fraud Detection jobs look for? The top searched job categories for Data Scientist Fraud Detection jobs are:
Data Scientist Fraud Detection jobs near you
Infographic showing various Data Scientist Fraud Detection job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist (Fraud)

Democrance

NY • On-site

$120 - $180/hr

Other

Medical, Retirement

Posted 3 days ago

New

Job description

Who we are

Ranked in 2024 by the Financial Times, Moniepoint is Africa’s fastest-growing fintech, trusted by over 10 million business and individual accounts, processing billions of Naira in transactions monthly. Our mission is to enable financial happiness for every African, everywhere.

About this role:

We're looking for a Data Scientist to sit at the heart of how we fight fraud — building the models, experiments, and detection systems that protect millions of customers and merchants across our platform. This is a high-impact role at the intersection of machine learning, product, and engineering, where your work will directly shape how Moniepoint detects and responds to emerging fraud threats.

You are a data-driven, intellectually curious Data Scientist who is energized by hard problems in fraud and financial crime. You'll prototype and ship ML models, design experiments, and uncover new fraud signals across our ecosystem — partnering closely with engineers, product managers, and analysts to turn your work into production-grade systems.

Responsibilities:

  • Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.

  • Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.

  • Size fraud typologies across our product lines to inform prioritization and investment decisions.

  • Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.

  • Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations.

Experience & Background:

  • A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).

  • 3+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime.

  • Hands-on experience building and deploying machine learning models in a production environment.

  • Fraud, risk, or financial services experience is a strong plus.

  • Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering.

  • Comfort working in fast-paced, cross-functional teams with high ownership expectations.

Skills & Competencies:

  • Proficiency in Python and SQL; comfort working across the full model development lifecycle.

  • An investigative instinct — you enjoy digging into data to find patterns others miss.

  • The ability to communicate technical findings clearly to non-technical stakeholders and translate insights into action.

What Success Looks Like in This Role:

  • Production-grade ML models and anomaly detection systems that effectively surface and mitigate novel fraud vectors before they scale.

  • Well-designed experiments that successfully balance customer experience against fraud loss reduction.

  • Clear sizing of fraud typologies that effectively drives product prioritization and strategic investment decisions.

  • Seamless cross-functional alignment where technical model outputs are consistently translated into real-world fraud mitigations.

Why Join Us?

  • Culture: We put our people first and prioritize the well‑being of every team member. We've built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.

  • Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.

  • Compensation: You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

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