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Data Scientist Fraud Detection Jobs (NOW HIRING)

Robinhood

Senior Data Scientist, Fraud

Menlo Park, CA · On-site

$187K - $220K/yr

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 ...

First Bank

Fraud Detection Analyst

Greensboro, NC · On-site

Oversee fraud detection performance and exercise independent judgment to escalate, prioritize, and ... Bachelor's degree in Data Science, Data Analytics, Computer Science, Business Analytics ...

New

Elite WorkForce Inc

Data Scientist at GA

Atlanta, GA · On-site

Data Scientist Location: Atlanta, GA 30334 Client: State of Georgia Duration: 12+ Months We are ... Develop and deploy machine learning models for fraud detection. * Collaborate with engineering and ...

Socure

Staff Data Scientist - Fraud & Risk

New York, NY · On-site

$180K - $210K/yr

... fraud detection and risk management solutions. You will lead technical initiatives, mentor peers ... Mentor and share knowledge with peers and junior data scientists, fostering a culture of ...

Mindlance

Data Scientist

San Francisco, CA · On-site

They are seeking a Data Scientist to develop predictive models in marketing, understand business ... The role involves using machine learning models for web content categorization and fraud detection.

OpenAI

Data Scientist, Integrity

San Francisco, CA · On-site

The Data Scientist, Integrity role involves designing and building systems for fraud detection and remediation, working closely with various teams to combat fraudulent activities on the platform.

Sam's Club

Data Scientist III

Bella Vista, AR

$90K - $180K/yr

We are looking for a Data Scientist III to join Sam's Club fraud detection team. As a Data Scientist III, you will be responsible for owning fraud risks in various product segments and being a ...

Sam's Club

Data Scientist III

Cassville, MO · On-site

$90K - $180K/yr

We are looking for a Data Scientist III to join Sam's Club fraud detection team. As a Data Scientist III, you will be responsible for owning fraud risks in various product segments and being a ...

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All JobsData Scientist Fraud Detection Jobs

Data Scientist Fraud Detection information

See salary details

$37.5K

$122.7K

$196.5K

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

As of Jun 17, 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, and why are they important?

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 June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $122,738 per year, or $59 per hour.
Senior Data Scientist, Fraud

Senior Data Scientist, Fraud

Robinhood

Menlo Park, CA

Other

Medical, Life, Retirement, PTO

Posted 17 days ago

Job description

About the team + role

We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Fraud Data Science team safeguards Robinhood and its customers by detecting and preventing fraud and abuse across our platform. We leverage machine learning and analytics to combat malicious behavior in real time, supporting a safe and trusted experience for all users. Our work has a direct impact on customer security, company risk posture, and regulatory compliance.

As a Senior Data Scientist on the Fraud team, you will own the design and deployment of ML solutions that proactively surface suspicious activity, reduce financial loss, and improve fraud detection precision. You'll collaborate closely with engineering, product, risk, and compliance partners to influence system architecture, shape policy through data, and enhance the safety and integrity of our platform.

This role is based in our Menlo Park office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you'll do
  • Design and deploy fraud detection models to protect Robinhood users and assets in real time
  • Analyze behavioral data to uncover emerging fraud vectors and support rapid incident response
  • Develop robust data pipelines and monitoring systems to ensure model accuracy and reliability
  • Partner with engineering and product teams to implement safeguards and user-facing features
  • Guide experimentation strategy and contribute to long-term fraud prevention roadmap
What you bring
  • 5+ years of experience in data science or applied ML, with a focus on fraud detection or risk mitigation
  • Advanced proficiency in Python and SQL; experience with ML frameworks like XGBoost, LightGBM, or TensorFlow
  • Strong statistical acumen with experience in anomaly detection, pattern recognition, and A/B testing
  • Excellent communication skills and ability to influence decision-making across technical and non-technical audiences
  • A collaborative mindset and proactive approach to navigating ambiguity in fast-paced environments
What we offer
  • Challenging, high-impact work to grow your career.
  • Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
  • Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
  • Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more.
  • Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
  • Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
  • Exceptional office experience with catered meals, events, and comfortable workspaces.


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