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Fraud Detection Machine Learning Jobs (NOW HIRING)

Affirm

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 ...

ExtendMyTeam

Machine Learning Engineer

Cary, NC

As a Machine Learning Engineer, you will help build and operate production systems that power fraud detection and risk-related products. You'll work closely with data scientists and engineers to ...

Mitek Systems

Sr. Machine Learning Engineer

$107K - $146K/yr

As a Sr. Machine Learning Engineer, you will lead applied ML initiatives that power our next ... You will help develop and improve systems designed to detect fraud, replay attacks, deepfakes, and ...

Mitek Systems

Sr. Machine Learning Engineer

Charleston, WV · Remote

$107K - $146K/yr

As a Sr. Machine Learning Engineer, you will lead applied ML initiatives that power our next ... You will help develop and improve systems designed to detect fraud, replay attacks, deepfakes, and ...

S.T.E.P.

Senior Machine Learning Engineer

Palo Alto, CA · On-site +1

You'll design, develop, and deploy machine learning models to enhance our Risk and Fraud detection systems. These models protect Step and our customers from fraud and financial loss. You'll take the ...

Extend

Senior Machine Learning Data Scientist

$135K - $165K/yr

As a Senior ML Data Scientist, you will own the development of cutting-edge machine learning models based on signals and transactions from hundreds of millions of users to detect and prevent fraud ...

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building ... This includes the core fraud detection model that decides the majority of our traffic, alongside ...

ID.me

Senior Fraud Investigations Analyst

Mclean, VA · On-site

Use fraud detection tools, machine learning outputs, and risk-scoring systems to drive high-quality investigations * Independently own investigations from detection through resolution, including ...

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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 Jun 14, 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 June 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $37,548 per year, or $18.1 per hour.
Manager, Machine Learning Engineering (Fraud)

Manager, Machine Learning Engineering (Fraud)

Affirm

Remote

$204K - $264K/yr

Full-time

Medical, Dental, Vision

Posted 20 days ago

Job description

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
The Fraud Machine Learning team builds models that power critical decisions during the loan application process, protecting Affirm and its customers from fraud while maintaining a seamless user experience. As a manager, you will lead a team of ML engineers developing and improving models that detect and prevent abuse in a rapidly evolving, adversarial environment.
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 production deployment and monitoring. You will partner closely with Product, Fraud Analytics, Risk, and Platform teams to ensure high-quality models are effectively integrated into decisioning systems. You will also help drive the evolution of modeling approaches at Affirm, including the adoption of representation learning and transformer-based techniques to better capture complex behavioral patterns.
What you'll do
  • Set the technical and modeling strategy for fraud detection, aligning team efforts with key business outcomes such as fraud loss reduction, approval rates, and customer experience
  • Lead a team of machine learning engineers to design, build, and iterate on high-impact fraud models across the full ML lifecycle, from experimentation to production
  • Drive the evolution of modeling approaches, including the adoption of representation learning, transformer-based methods, and other advanced techniques for modeling complex behavioral data
  • Partner cross-functionally with Product, Fraud Analytics, Risk, and Engineering to define solutions, evaluate trade-offs, and ensure models are effectively integrated into decisioning systems
  • Develop talent by coaching engineers, providing feedback, and fostering a high-performing team culture grounded in technical excellence and ownership

What we look for
  • Bachelor's in a technical field with 8+ years of industry experience, including 3+ years managing engineers
  • Experience with modern ML approaches, including representation learning, deep learning, or transformer-based models, as well as traditional methods such as gradient-boosted trees
  • Proven ability to lead teams delivering end-to-end ML solutions in production environments, including experimentation, evaluation, and model iteration in production
  • Strong engineering fundamentals and experience working with scalable systems and data pipelines
  • Track record of effective cross-functional collaboration with product, analytics, and engineering partners
  • Ability to operate in ambiguous, fast-evolving environments and drive clarity, prioritization, and execution
  • This position requires either equivalent practical experience or a Bachelor's degree in a related field.

Pay Grade - P
Equity Grade - 13
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $230,000 - $290,000
USA base pay range (all other U.S. states) per year: $204,000 - $264,000
#LI-Remote
Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.
We're extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
  • Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
  • Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
  • Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
  • ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

We believe It's On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

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