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Fraud Detection Machine Learning Jobs in Arizona

BloKchain Talent

Anti-Fraud Risk Engineer

Tempe, AZ · On-site

Teamwork with different function teams to design abuse, porn, tele-fraud detection model base on ... And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc. * The basic ...

BloKchain Talent

Anti-Fraud Risk Engineer

Tempe, AZ · On-site

Teamwork with different function teams to design abuse, porn, tele-fraud detection model base on ... And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc. * The basic ...

Varsity Tutors

Machine Learning Tutor

Chandler, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Scottsdale, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Tempe, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Glendale, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Mesa, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Phoenix, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Tucson, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Gilbert, AZ · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Phoenix Staff

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

... machine learning pipelines for risk modeling, utilization forecasting, fraud detection, quality measurement, and care gap analysis. · Operationalize models with strong MLOps practices including ...

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Arizona

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 Arizona is $16.82, according to ZipRecruiter salary data. Most workers in this role earn between $13.89 and $17.93 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.
What are popular job titles related to Fraud Detection Machine Learning jobs in Arizona? For Fraud Detection Machine Learning jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Arizona look for? The top searched job categories for Fraud Detection Machine Learning jobs in Arizona are:
What cities in Arizona are hiring for Fraud Detection Machine Learning jobs? Cities in Arizona with the most Fraud Detection Machine Learning job openings:
Fraud Detection Machine Learning jobs near you

Anti-Fraud Risk Engineer

BloKchain Talent

Tempe, AZ • On-site

Full-time

Re-posted 28 days ago

Job description

Company Description

Our Client, is an award-winning workplace. They have been recognized by Comparably as #1 CEO, Company Happiness, Benefits, Compensation, Diversity, and more! Not to mention they've been awarded by Glassdoor as the 2nd Best US workplace & Best Large Company US CEO in 2018, Wealthfront, and Business Insider. They culture focuses on delivering happiness, our commitment to transparency, and the tangible benefits we provide our employees and our customers.

Job Description

POSITION TITLE: Anti-Fraud Risk Engineer
LOCATION: Phoenix AZ 
SALARY: Based on Experience 
SPONSORSHIP: No 
Responsibilities:

  • Teamwork with different function teams to design abuse, porn, tele-fraud detection model base on different business product requirement and protection policy.
  • Responsible for developing telephone anti-fraud, anti-spam, anti-pornography, anti-abuse registration and other services
  • Responsible for the implementation and practice of related algorithms under the current mainstream stream computing platform
Qualifications
  • Master's degree + 2 years working experience in machine learning
  • Proficiency in at least one programming language such as Java, Python
  • Proficiency in big data, the use of frameworks related to stream computing, such as Spark, Flink, etc. And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc.
  • The basic algorithms and deep learning algorithms of related machine learning have a deep understanding and mastery, and require the use of related algorithms, experience in the processing of common procedures in feature engineering, and excellent engineering practice capabilities
  • Experience in algorithms such as, anti-fraud, telecommunication risk control, recommendation system, advertising orientation, click model, etc. is preferred
  • Strong research capabilities, such as high-quality papers published in the field ** conferences such as CVPR, ICCV, ICML, NIPS, etc.
  • ACMICPC, NOI / IOI, Top coder, Kaggle competition winners are preferred
  • Research experience related to graph learning and few-shot learning is preferred
  • Language requirement: English, Mandarin is plus
Additional Information

All your information will be kept confidential according to EEO guidelines.

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