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Fraud Detection Machine Learning Jobs in Evanston, IL

TigerGraph

Account Executive

Chicago, IL · On-site

$150K - $160K/yr

Its proven technology supports fraud detection, customer 360, MDM, IoT, machine learning, and of course AI. TigerGraph clients leverage its technology to efficiently and accurately harness the true ...

Adyen

Associate Fraud Analyst

Chicago, IL · On-site

$36 - $47/hr

... to detect and mitigate fraudulent activity in real-time. * Assist in the development and ... learning from each other, while also supporting flexibility. Diversity, Equity, and Inclusion at ...

Adyen

Associate Fraud Analyst

Chicago, IL · On-site

$36 - $47/hr

... to detect and mitigate fraudulent activity in real-time. * Assist in the development and ... learning from each other, while also supporting flexibility. Diversity, Equity, and Inclusion at ...

Socket.dev

Machine Learning Engineer

Oakbrook Terrace, IL · On-site

$110 - $145/hr

We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional ... Support model performance monitoring, drift detection, and retraining cycles Deployment, Monitoring ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Implement anomaly detection for real‑time quality monitoring during automated assembly * Optimize ...

Crowe

Machine Learning Intern

Chicago, IL

$27 - $42/hr

Anomaly detection using deep neural networks Numerical optimization applied to problems in manufacturing Personal identifiable information (PII) and personal health information (PHI) detection in ...

Crowe

Machine Learning Intern

Chicago, IL · On-site

Anomaly detection using deep neural networks Numerical optimization applied to problems in manufacturing Personal identifiable information (PII) and personal health information (PHI) detection in ...

Crowe LLP

Machine Learning Intern

Chicago, IL · On-site

Anomaly detection using deep neural networks Numerical optimization applied to problems in manufacturing Personal identifiable information (PII) and personal health information (PHI) detection in ...

Crowe LLP

Machine Learning Intern

Oakbrook Terrace, IL · On-site

$27 - $42/hr

Anomaly detection using deep neural networks Numerical optimization applied to problems in manufacturing Personal identifiable information (PII) and personal health information (PHI) detection in ...

Crowe LLP

Machine Learning Intern

Chicago, IL · On-site

$27 - $42/hr

Anomaly detection using deep neural networks Numerical optimization applied to problems in manufacturing Personal identifiable information (PII) and personal health information (PHI) detection in ...

Doist

Senior Data Scientist - Fraud (Hybrid)

Chicago, IL · On-site

$96 - $125/hr

Partner closely with Fraud Operations through the full detection loop -- pulling data together ... Requirements: * 4+ years of experience in analytics, applied machine learning, or quantitative ...

1 point system

Senior Data Scientist

Chicago, IL · Remote

The Sr Data Scientist will design and implement machine learning and NLP solutions for a claims and ... Experience with insurance claims, risk management analytics, litigation analytics, fraud detection ...

TransUnion

AI Research & Innovation Lead

Chicago, IL · On-site

Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Cognitive ... Familiarity with consumer data, fraud detection, financial services, risk analytics, identity, or ...

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Showing results 21-40

All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Evanston, IL

Fraud Detection Machine Learning information

See Evanston, IL salary details

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

As of Sep 4, 2026, the average hourly pay for fraud detection machine learning in Evanston, IL is $17.32, according to ZipRecruiter salary data. Most workers in this role earn between $14.28 and $18.46 per hour, depending on experience, location, and employer.

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 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 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 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 cities near Evanston, IL are hiring for Fraud Detection Machine Learning jobs?

Cities near Evanston, IL with the most Fraud Detection Machine Learning job openings:

Fraud Detection Machine Learning jobs near you

Account Executive

TigerGraph

Chicago, IL • On-site

$150K - $160K/yr

Full-time

Posted 28 days ago

Key responsibilities

  • Define and execute sales plans for assigned accounts and territory

  • Manage and track customer information in the CRM system and provide activity forecasts and pipeline reports

  • Manage renewals and develop account plans for large assigned accounts

Job description

TigerGraph is the premier enterprise and SaaS platform for advanced analytics, context,  and machine learning on connected data. TigerGraph's core technology is the only scalable graph database to connect  the enterprise. Its proven technology supports fraud detection, customer 360, MDM, IoT, machine learning, and of course AI.  TigerGraph clients leverage its technology to efficiently and accurately harness the true power, accuracy and probability of AI.

Global Banks, Fortune 500 organizations, and the most innovative mid-size and startup companies choose TigerGraph to accelerate their analytics, AI,machine learning, and indeed decisioning.

  • Seven of the top ten global banks use TigerGraph for real-time fraud detection.
  • 50 million patients receive care path recommendations to assist them on a wellness journey.
  • 300 million consumers receive personal offer recommendations powered by TigerGraph.
  • TigerGraph reduces power outages by optimizing energy infrastructure for 1 billion people.

Responsibilities

  • Define and execute sales plans for assigned accounts and territory
  • Meet and exceed quota through prospecting, qualifying, managing and closing sales opportunities within assigned accounts and territory
  • Develop account plans for large assigned accounts
  • Manage renewals in existing assigned accounts
  • Understand the competitive market and industry trends
  • Manage and track customer information in the TigerGraph CRM system
  • Provide activity forecasts and regular pipeline reporting in sales meetings and through the CRM system
  • Other duties as assigned

Required Education and Experience

  • Bachelor's Degree or equivalent required
  • 15+ years of enterprise software sales experience
  • Experience formulating and selling large contracts
  • Advanced degrees and/or technical expertise valued
  • Understanding and ability to sell enterprise and SaaS contracts from lead to closed sale

Qualifications

  • Track record of closing sales with companies with revenue of $500M+
  • Experience selling to C-suite executives
  • Experience selling into financial institutions
  • Understanding of AI, ML and  Database & Cloud based solutions a plus
  • Consistent overachievement of sales goals in a large geographic territory
  • Drive to expand client base and close sales
  • Excellent verbal and written communication skills
  • Entrepreneurial, strong work ethic, resourceful
  • Willing to travel to clients to develop and support customers
  • Coachability as well as creativity
  • High Emotional Intelligence
  • Strong desire to understand complex client ecosystems and successfully navigate within those systems
  • A commitment to continuous improvement

The anticipated salary range for candidates is $150,000-$160,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to, the type and length of experience within the job, type and length of experience within the industry, education, etc.