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Fraud Detection Machine Learning Jobs (NOW HIRING)

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Manager, Machine Learning Engineering (Fraud)

$204K - $264K/yr

In this role, you will define the technical and modeling strategy for fraud detection, guiding the team across the full machine learning lifecycle from feature development and experimentation to ...

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Fraud Detection Machine Learning information

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How much do fraud detection machine learning jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for fraud detection machine learning in the United States is $18.05, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $19.23 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working in fraud detection machine learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are the key skills and qualifications needed to thrive as a fraud detection machine learning specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.
More about Fraud Detection Machine Learning jobs
What cities are hiring for Fraud Detection Machine Learning jobs? Cities with the most Fraud Detection Machine Learning job openings:
What states have the most Fraud Detection Machine Learning jobs? States with the most job openings for Fraud Detection Machine Learning jobs include:
What job categories do people searching Fraud Detection Machine Learning jobs look for? The top searched job categories for Fraud Detection Machine Learning jobs are:
Fraud Detection Machine Learning jobs near you
Infographic showing various Fraud Detection Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $37,548 per year, or $18.1 per hour.

Data Scientist III - Fraud Analytics & Machine Learning

Sam's Club

Greenland, AR • On-site

Full-time

Posted 4 days ago

Sam's Club rating

6.4

Company rating: 6.4 out of 10

Based on 2,014 frontline employees who took The Breakroom Quiz

17th of 39 rated national retailers

Job description

Position Summary... What you'll do...Fraud Analytics & Machine Learning | Walmart Global Tech Help Shape the Future of Retail Intelligence

Every day, millions of customers trust Walmart to deliver a seamless shopping experience. Behind that experience is one of the world's largest and most sophisticated commerce ecosystems—and protecting it from fraud requires exceptional data scientists.

As a Data Scientist III on the Inkiru Data Science team, you'll transform billions of data points into intelligent solutions that identify fraud, reduce risk, and protect both customers and the business. You'll partner with engineers, product managers, and business leaders to build analytics and machine learning solutions that directly influence decisions at global scale.

If you're energized by solving complex problems, uncovering meaningful insights, and seeing your work deployed into production, we'd love to meet you.

Why This Role Matters

Fraud evolves every day—and so do we.

Our team combines advanced analytics, statistical modeling, machine learning, and AI to stay ahead of emerging threats while delivering a seamless experience for customers and associates.

Your work won't sit in a report.

It will power real products, influence strategic decisions, and help protect one of the largest retailers in the world.

What You'll Do

You'll make an impact by:

  • Detecting emerging fraud trends using large-scale behavioral, transactional, and operational data.

  • Building analytical models that improve fraud detection, risk management, and business decision-making.

  • Creating intuitive dashboards and visualizations that help leaders quickly understand key business metrics.

  • Partnering closely with Product, Engineering, Data Science, and Business teams to bring analytical solutions into production.

  • Exploring new analytical techniques—including machine learning and AI—to solve evolving business challenges.

  • Improving data quality through validation, governance, and scalable analytical processes.

  • Communicating complex findings through compelling storytelling that drives action.

What You'll Work With

You'll leverage modern technologies including:

  • Python

  • SQL

  • Spark

  • Hive

  • BigQuery

  • Distributed computing platforms

  • Tableau

  • Power BI

  • Machine Learning frameworks

  • Cloud-scale analytics platforms

  • AI-assisted analytics and modern data science workflows

Why You'll Love This Team

You'll join a collaborative team that values curiosity, experimentation, and continuous learning.

Here you'll have opportunities to:

  • Solve problems at one of the largest scales in retail.

  • Work with experienced data scientists and machine learning engineers.

  • Influence product strategy with data-driven insights.

  • Build solutions that move from concept into production.

  • Learn new technologies while working on meaningful business challenges.

  • Grow your career through mentorship, leadership opportunities, and cross-functional collaboration.

What Success Looks Like

Within your first year, you'll:

  • Deliver analytical solutions that influence fraud strategy.

  • Build trusted relationships across Product, Engineering, and Business teams.

  • Create scalable dashboards and reporting used by leadership.

  • Improve fraud detection through innovative analytical approaches.

  • Contribute to production-ready data science solutions that create measurable business value.

What You'll Bring

We're looking for someone who combines technical excellence with curiosity and business acumen.

Preferred qualifications include:

  • Strong analytical and statistical problem-solving skills.

  • Experience working with large, complex datasets.

  • Proficiency in SQL and Python (R is also welcome).

  • Experience with distributed computing technologies such as Spark, Hive, or BigQuery.

  • Familiarity with data visualization tools including Tableau, Power BI, or Looker.

  • Ability to communicate technical concepts clearly to both technical and non-technical audiences.

  • Passion for solving ambiguous problems using data.

  • Bachelor's degree in a STEM field with 3+ years of relevant experience, or a Master's degree with 1+ years of experience.

Bonus Points If You Have

  • Experience in fraud analytics, financial risk, cybersecurity, or trust and safety.

  • Experience building or deploying machine learning models.

  • Knowledge of experimentation, causal inference, or advanced statistical techniques.

  • Experience with Generative AI, LLMs, or AI-assisted analytics.

  • Experience working in cloud-native data environments.

Why Walmart Global Tech

Technology is reshaping how the world shops.

At Walmart Global Tech, you'll help solve problems that few companies can match in complexity or scale. Our teams build products and platforms that serve millions of customers, associates, and suppliers every day.

Here, your work has immediate impact.

You'll have access to world-class data, modern technologies, and talented teammates—all while helping build the future of retail.

Whether your passion is analytics, machine learning, artificial intelligence, or data engineering, you'll find opportunities to learn, innovate, and grow your career.

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Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics or related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field. Option 3: 4 years' experience in an analytics or related field. Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture. Primary Location... 2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

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