1

Fraud Risk Jobs in Chicago, IL (NOW HIRING)

Machine Learning Lead

Chicago, IL · On-site

$175K - $235K/yr

Coinflow is seeking a Machine Learning Lead to own the fraud and risk intelligence layer at the core of our platform. This is a founding ML role. You'll lead our first dedicated ML team, building ...

Machine Learning Lead

Chicago, IL · On-site

$225K - $275K/yr

Coinflow is seeking a Machine Learning Lead to own the fraud and risk intelligence layer at the core of our platform. This is a founding ML role. You'll lead our first dedicated ML team, building ...

Machine Learning Lead

Chicago, IL · On-site

$225K - $275K/yr

The Role Coinflow is seeking a Machine Learning Lead to own the fraud and risk intelligence layer at the core of our platform. This is a founding ML role. You'll lead our first dedicated ML team ...

... fraud risk, and physical security risk management. What You'll Be Doing * Support recurring US ORM program execution activities, including RCSA program reporting, operational loss metrics and related ...

Risk Manager

Chicago, IL · On-site

$105K - $132K/yr

Risk Mitigation & Process Optimization: Design, implement, and continuously refine robust risk ... Advanced Theft & Fraud Prevention: Lead the implementation and monitoring of cutting-edge practices ...

The ideal candidate combines deep fraud and payments risk domain expertise with strong cross-functional instincts. Responsibilities * Monitor and Mitigate Risk: Identify churn signals, integration ...

The ideal candidate combines deep fraud and payments risk domain expertise with strong cross-functional instincts. Responsibilities * Monitor and Mitigate Risk: Identify churn signals, integration ...

Who We Want Arrive Logistics is seeking a proactive, collaborative, and detail-oriented Risk Manager to protect our operations against carrier fraud, strategic cargo theft, and operational risk. In ...

Design and optimize risk-based identity verification workflows using data-driven decisioning to balance approval rates, customer friction, and fraud loss. * Evaluate and integrate third-party ...

Design and optimize risk-based identity verification workflows using data-driven decisioning to balance approval rates, customer friction, and fraud loss. * Evaluate and integrate third-party ...

Showing results 41-60

Fraud Risk information

See Chicago, IL salary details

$14

$31

$76

How much do fraud risk jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for fraud risk in Chicago, IL is $31.25, according to ZipRecruiter salary data. Most workers in this role earn between $20.05 and $39.86 per hour, depending on experience, location, and employer.

What is fraud risk?

Fraud risk refers to the possibility that an individual or organization will intentionally deceive others for financial or personal gain. A fraud risk analyst is responsible for identifying, assessing, and mitigating risks related to fraudulent activities within a company or financial institution. Their duties typically include monitoring transactions, analyzing data patterns, developing anti-fraud policies, and working with law enforcement or regulatory agencies to investigate suspicious activities. By proactively managing fraud risk, these professionals help protect their organization’s assets and reputation.

What are the key skills and qualifications needed to thrive as a fraud risk analyst?

To thrive as a Fraud Risk Analyst, you need strong analytical skills, attention to detail, and a background in finance, accounting, or a related field, often supported by a relevant degree. Familiarity with fraud detection software, data analytics tools (like SQL, SAS, or Python), and certifications such as Certified Fraud Examiner (CFE) are typically required. Excellent problem-solving, communication, and critical thinking skills help you proactively identify risks and work effectively with cross-functional teams. These abilities are crucial for detecting and mitigating fraudulent activities, protecting organizational assets, and maintaining regulatory compliance.

What are some common challenges faced by professionals in fraud risk roles, and how can they be addressed?

Professionals in Fraud Risk roles often encounter challenges such as staying ahead of rapidly evolving fraud tactics, managing large volumes of data, and balancing the need for security with customer experience. To address these, it’s crucial to continuously update knowledge on emerging threats, leverage advanced analytical tools, and collaborate closely with IT, compliance, and customer service teams. Regular training, cross-department communication, and investment in technology can help ensure effective fraud detection and prevention while maintaining positive client interactions.

What is the difference between Fraud Risk vs Fraud Analyst?

AspectFraud RiskFraud Analyst
Required CredentialsRisk management certifications, knowledge of fraud preventionCertifications like CFE, CPA, or fraud examination credentials
Work EnvironmentRisk assessment teams, compliance departmentsInvestigations, data analysis, reporting
Employer & Industry UsageFinancial institutions, insurance, retailBanking, finance, insurance, retail

Fraud Risk focuses on identifying and managing potential vulnerabilities to fraud within an organization, emphasizing risk assessment and mitigation strategies. Fraud Analysts, on the other hand, investigate specific fraud cases, analyze data, and detect fraudulent activities. While both roles require knowledge of fraud prevention, Fraud Risk professionals develop strategies to prevent fraud, whereas Fraud Analysts handle the detection and investigation of actual incidents.

What are the most commonly searched types of Fraud Risk jobs in Chicago, IL?

The most popular types of Fraud Risk jobs in Chicago, IL are:

What job categories do people searching Fraud Risk jobs in Chicago, IL look for?

The top searched job categories for Fraud Risk jobs in Chicago, IL are:

Infographic showing various Fraud Risk job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $65,002 per year, or $31.3 per hour.

Machine Learning Lead

Chicago, IL • On-site

$175K - $235K/yr

Other

Medical, Retirement

Posted 23 days ago


Key responsibilities

  • Own the development, deployment, and improvement of fraud detection and risk decisioning models.

  • Define, track, and enhance core fraud and risk metrics such as detection rate, false positive rate, and chargeback rate.

  • Collaborate with engineering, product, and operations teams to integrate fraud intelligence into payment flows and internal tools.


Job description

About Coinflow

Coinflow is the next-generation payment service provider revolutionizing global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant settlement. Coinflow enables businesses to grow faster with instant settlement, fraud & chargeback indemnity, global pay-ins, multi-currency FX, and unified payouts. Founded in 2023, the company serves marketplaces, fintechs, remittance providers, gaming platforms, and ecommerce merchants worldwide.

Since our seed round in 2024, we’ve achieved 23x revenue growth and scaled to multi-billion-dollar annual transaction volume. In response to this growth, Coinflow announced a $25M Series A in October 2025—led by Pantera Capital, CMT Digital, Coinbase Ventures, Jump Crypto, and Reciprocal Ventures—accelerating our mission to power the world’s fastest-moving businesses with innovative, reliable global payments.

Coinflow is proudly headquartered in Chicago, IL.

Role Overview:

Coinflow is seeking a Machine Learning Lead to own the fraud and risk intelligence layer at the core of our platform.

This is a founding ML role. You'll lead our first dedicated ML team, building capabilities that combine our first-party transaction data with partner signals to optimize approval rates across payment methods and geographies, sharpen risk decisioning during merchant underwriting, and improve fraud detection across global payment methods. That means digging into large-scale transaction and behavioral data, shipping production fraud models, defining what good looks like, and continuously raising the bar on detection and precision as our volume and merchant base scale.

The ideal candidate has hands-on experience building fraud models on the acquiring side of payments and working alongside external fraud vendors to tackle card-present or card-not-present fraud, authorization decisioning, chargeback reduction, and related risk systems.

Key Responsibilities
  • Strengthen Coinflow's fraud detection and risk decisioning capabilities — feature engineering, model development, and production deployment
  • Own the full model lifecycle: experimentation, evaluation, monitoring, and iteration
  • Define and track core fraud and risk metrics — detection rate, false positive rate, chargeback rate, dispute win rate — and continuously improve them
  • Explore transaction and behavioral data to surface new fraud signals and emerging attack patterns
  • Partner with Engineering, Product, and Operations to embed fraud intelligence directly into payment flows and internal tooling
  • Integrate and orchestrate external fraud/risk partners, getting maximum value from their tooling
  • Establish the foundation for ML and data practices across the company
  • Help shape Coinflow's long-term fraud, risk, and ML roadmap
Required Qualifications
  • 5+ years in machine learning, applied data science, or production ML roles
  • Demonstrated experience building fraud models in payments, with direct exposure to the acquiring side — acquirer, PSP, or payment facilitator
  • Proven track record taking ML projects from proof-of-concept to fully deployed, productionized systems
  • Deep familiarity with acquiring-side fraud dynamics: authorization fraud, card-not-present fraud, friendly fraud, chargeback patterns, and merchant risk
  • Strong foundation in ML, statistics, and feature engineering on high-volume financial data
  • Comfortable owning ambiguous problems end-to-end and creating structure where none exists
  • Strong collaborator across Engineering, Product, and Ops
Preferred Qualifications
  • Experience at an acquirer, ISO, PayFac, or payments infrastructure company
  • Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining schedules, real-time performance metrics)
  • Experience scoping cloud compute requirements for scalable ML workloads
  • Familiarity with card network rules, dispute/chargeback workflows, and fraud liability frameworks
  • Experience as an early or sole ML hire at a startup
  • Exposure to real-time or near-real-time fraud scoring systems
  • Experience with stablecoin, crypto, or alternative payment rails

What We Offer:

  • Competitive compensation including base salary, performance bonus, and meaningful ownership
  • Opportunity to build the fraud and risk intelligence layer of a rapidly scaling fintech company
  • Collaborative and innovative work environment with world-class investors
  • Direct impact on core risk infrastructure and company trajectory during a hyper growth phase

The base salary range for this role is $175,000 to $235,000 USD. The actual base salary offered depends on a variety of factors, including but not limited to experience, education, skills, qualifications and business needs.

In addition, the employee who fills this role will be eligible for an equity grant, allowing you to share in the long-term success of the company. You will also have access to a wide array of benefits, including health and wellness benefits, 401(k) savings plan, and flexible time off.

#J-18808-Ljbffr