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Ai Artificial Intelligence Fraud Detection Jobs (NOW HIRING)

Blue Shield of California

AI Auditor, Senior

Oakland, CA · On-site

$90K - $136K/yr

The AI Internal Audit Consultant will support audit, compliance, fraud detection, and investigative activities focused on the use and misuse of artificial intelligence systems. In this role, you will ...

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

Description Position Summary The Assistant Vice President of Artificial Intelligence (AVP of AI) is ... Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit ...

Weave

Fraud Analyst

Lehi, UT · On-site

Suspicious Merchant Activity Detection: Proactively monitor merchant accounts for anomalous ... At Weave, we use Artificial Intelligence (AI) tools to help us work more efficiently and create a ...

US Bank

Prepaid Fraud Risk Manager

Tempe, AZ

... artificial intelligence, machine learning, and advanced analytics to improve fraud detection ... Utilize approved AI tools, analytics platforms, and digital solutions responsibly, validating ...

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Ai Artificial Intelligence Fraud Detection information

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How much do ai artificial intelligence fraud detection jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for ai artificial intelligence fraud detection in the United States is $57.05, according to ZipRecruiter salary data. Most workers in this role earn between $49.04 and $63.70 per hour, depending on experience, location, and employer.

What is AI artificial intelligence fraud detection?

AI Fraud Detection refers to the use of artificial intelligence technologies to identify and prevent fraudulent activities in various sectors such as banking, insurance, and e-commerce. These systems analyze large volumes of data, detect unusual patterns, and flag potentially fraudulent transactions more quickly and accurately than traditional methods. Machine learning algorithms continuously improve by learning from new data, helping organizations reduce financial losses and enhance security. AI-based fraud detection can be applied in real-time, making it an essential tool for mitigating risks and maintaining customer trust.

What are the key skills and qualifications needed to thrive as an AI artificial intelligence fraud detection specialist?

To excel in AI Fraud Detection, you need a solid background in data science, machine learning, and cybersecurity, typically supported by a degree in computer science or related fields. Expertise in programming languages like Python or R, experience with machine learning frameworks (e.g., TensorFlow, scikit-learn), and familiarity with fraud detection systems are essential. Strong analytical thinking, problem-solving, and effective communication skills help professionals interpret complex data and work with cross-functional teams. These capabilities are crucial for accurately identifying fraudulent activity, minimizing risks, and maintaining organizational security.

What are the typical challenges faced when working in AI-driven fraud detection roles?

Professionals in AI fraud detection often encounter challenges such as adapting to rapidly evolving fraud tactics and ensuring their models can accurately detect new, sophisticated schemes. Balancing the need to minimize false positives—so legitimate transactions are not wrongly flagged—with catching actual fraudulent activity requires constant model tuning and data analysis. Additionally, collaboration with cross-functional teams, such as cybersecurity, compliance, and customer support, is essential to ensure comprehensive solutions and swift incident response. Staying updated with the latest industry trends and regulatory requirements also plays a big role in everyday work.

What is the difference between Ai Artificial Intelligence Fraud Detection vs Data Analyst?

AspectAi Artificial Intelligence Fraud DetectionData Analyst
Required CredentialsBachelor's in Computer Science, Data Science, or related fields; certifications in AI or machine learningBachelor's in Statistics, Mathematics, or related fields; data analysis certifications
Work EnvironmentTech companies, financial institutions, cybersecurity firmsBusiness, finance, healthcare, or marketing departments across various industries
Employer & Industry UsageUsed for detecting fraud patterns using AI algorithmsUsed for interpreting data trends, reporting, and supporting decision-making

Ai Artificial Intelligence Fraud Detection specialists focus on developing and implementing AI systems to identify fraudulent activities, often requiring technical skills in machine learning. Data Analysts interpret data to uncover insights and support business strategies. While both roles work with data, AI Fraud Detection is more technical and specialized in AI applications, whereas Data Analysts focus on data interpretation and reporting.

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Ai Artificial Intelligence Fraud Detection jobs near you
Infographic showing various Ai Artificial Intelligence Fraud Detection job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $118,660 per year, or $57 per hour.

Data Scientist - AI/ML & Advanced Analytics (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA • Remote

Full-time

Retirement, PTO

Re-posted 9 days ago

Job description

Location: Remote (Occasional Travel May Be Required)
Clearance: Ability to obtain and maintain a Public Trust
Position Overview
Praescient Analytics is building a multidisciplinary advanced analytics team supporting federal fraud detection and investigative missions. We are seeking experienced Data Scientists with expertise in one or more advanced analytical disciplines, including artificial intelligence (AI), machine learning (ML), natural language processing (NLP), large language models (LLMs), graph analytics, and relationship discovery.
These positions will help design and implement next-generation analytical capabilities that identify hidden fraud patterns, uncover complex relationships, analyze unstructured information, and transform large, diverse datasets into actionable intelligence for investigators and oversight organizations.
The ideal candidate is a hands-on technical specialist who enjoys applying emerging analytical technologies to solve complex fraud, financial crime, and investigative challenges.
Key Responsibilities
  • Design, develop, validate, and optimize advanced analytical models supporting fraud detection and investigative missions.
  • Apply machine learning, artificial intelligence, natural language processing, graph analytics, and statistical modeling techniques to identify fraud patterns and emerging risks.
  • Analyze structured, semi-structured, and unstructured data from multiplegovernment and commercial sources.
  • Develop scalable analytical workflows using cloud-native technologies and open-source data science frameworks.
  • Collaborate with Graph Data Scientists, Data Engineers, Investigative Analysts, and Technical Analytics Managers to develop integrated analytical solutions.
  • Document analytical methodologies, model performance, validation results, and technical recommendations.
  • Support Agile software development through sprint planning, demonstrations, peer reviews, and iterative solution development.

Required Qualifications
  • Must have experience with Fraud Analysis
  • Three (3) or more years of professional experience developing advanced analytical or machine learning solutions.
  • Strong Python and SQL programming experience.
  • Experience developing, testing, validating, and improving analytical or machine learning models.
  • Experience working with cloud analytics environments.
  • Excellent analytical, written, and verbal communication skills.

Desired Experience
We are seeking candidates with demonstrated expertise in one or more of the following advanced analytics areas:
  • Artificial Intelligence & Machine Learning: Developing, validating, deploying, and optimizing machine learning and AI models using modern frameworks and best practices for predictive analytics, classification, clustering, and model evaluation.
  • Natural Language Processing (NLP) & Large Language Models (LLMs): Applying NLP, LLMs, Retrieval-Augmented Generation (RAG), semantic search, information extraction, document intelligence, and other techniques to analyze and derive insights from unstructured text.
  • Graph Analytics & Relationship Discovery: Leveraging graph databases, knowledge graphs, link analysis, network analytics, entity resolution, and relationship discovery tools (e.g., Neo4j, Cypher, i2 Analyst's Notebook) to identify hidden patterns and complex fraud networks.
  • Cloud-Native Analytics: Developing analytical solutions within modern cloud and Lakehouse environments using platforms such as Azure Databricks, Microsoft Fabric, Azure Data Lake Storage, SQL Server, Power BI, Git, or comparable technologies.
  • Fraud Analytics & Investigative Support: Applying advanced analytics to fraud detection, financial crimes, program integrity, federal benefit programs, grants, loans, emergency relief, or other government oversight and investigative missions.

What We're Looking For
We're looking for technically curious data scientists who enjoy exploring emerging technologies and applying them to real-world investigative challenges. Whether your expertise lies in machine learning, large language models, graph analytics, relationship discovery, or advanced AI techniques, you'll help build innovative analytical capabilities that strengthen government oversight, accelerate fraud detection, and support investigators in protecting the integrity of federal programs.
What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies

Benefits:
  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements. Praescient does not unlawfully discriminate or provide disparate treatment based on race, ethnicity, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
Praescient Analytics acknowledges the applicable clause and provision updates implementing Executive Order 14398, Addressing DEI Discrimination by Federal Contractors, and the related FAR/RFO updates, including FAR 52.222-90 where applicable. Praescient does not engage in racially discriminatory DEI activities, including disparate treatment based on race or ethnicity in recruitment, hiring, promotion, contracting, program participation, training, mentoring, leadership development, or allocation of company resources. Praescient's employment and contracting decisions are made based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
US Citizenship Required
Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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