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Ai Risk Analyst Jobs in Romeoville, IL (NOW HIRING)

... AI-assisted workflows that carry much of the operational load, and you develop the analysts and ... Own the fraud risk strategy and the end-to-end defense architecture across the payments stack ...

AI Model Risk Validation Specialist

Chicago, IL · Hybrid

$100K - $135K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Support inquiries with technical analysis and evidence Qualifications: * 5+ years in data science, model risk management, or AI/ML validation * Experience working with predictive models in regulated ...

Sr IT Auditor

Chicago, IL · On-site

$91K - $126K/yr

  • Medical

  • Life

  • Retirement

... AI risk and control strengths and concerns to peers, supervisors, and clients. * Partners with the Data Analytics team to leverage advanced analytics techniques in IT and AI audit approaches ...

Investments Risk, Principal

Chicago, IL · On-site

$175K - $215K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... AI-assisted tools as appropriate. * Contribute to risk and portfolio construction analysis to support manager evaluation and investment decisions. * Monitor and interpret risk exposures, factor ...

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Ai Risk Analyst information

See Romeoville, IL salary details

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How much do ai risk analyst jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for ai risk analyst in Romeoville, IL is $41.28, according to ZipRecruiter salary data. Most workers in this role earn between $30.38 and $50.24 per hour, depending on experience, location, and employer.

How does an AI risk analyst collaborate with cross-functional teams to assess and mitigate risks?

AI Risk Analysts work closely with data scientists, engineers, compliance officers, and business leaders to identify, evaluate, and mitigate risks associated with AI systems. They facilitate risk assessment workshops, gather input from technical and non-technical stakeholders, and ensure that risk controls are integrated into AI development processes. Effective communication and documentation are crucial, as analysts must translate complex technical risks into actionable recommendations for diverse teams. This collaborative approach helps ensure that AI solutions are both innovative and aligned with regulatory and ethical standards.

What is the difference between Ai Risk Analyst vs Data Scientist?

AspectAi Risk AnalystData Scientist
Required CredentialsBachelor's in Risk Management, Data Science, or related fields; certifications in AI or risk analysisBachelor's or Master's in Data Science, Statistics, or Computer Science; certifications in data analysis or machine learning
Work EnvironmentFinancial institutions, insurance companies, or tech firms focusing on risk assessmentTech companies, research labs, or any industry leveraging data for insights
Employer & Industry UsagePrimarily in finance, insurance, and risk-focused sectorsAcross various industries including tech, healthcare, finance, and marketing

The main difference is that an Ai Risk Analyst specializes in assessing and managing risks related to AI systems, often within financial or risk-focused industries. In contrast, a Data Scientist analyzes large datasets to extract insights across diverse sectors. While both roles require strong analytical skills and knowledge of AI and data tools, the Ai Risk Analyst focuses more on risk mitigation specific to AI applications.

What skills and qualifications are needed to be an AI risk analyst?

To thrive as an AI Risk Analyst, you need a strong foundation in data analysis, risk assessment, and an understanding of AI/ML technologies, typically supported by a degree in computer science, statistics, or a related field. Familiarity with risk management frameworks, AI auditing tools, and certifications such as CRISC or AI ethics credentials is often required. Excellent problem-solving, critical thinking, and communication skills help in identifying risks and conveying complex findings to stakeholders. These skills are crucial to ensure responsible AI deployment, mitigate potential risks, and maintain regulatory compliance.

What is an AI risk analyst?

AI Risk Analysts are professionals who assess, monitor, and manage the risks associated with the development and deployment of artificial intelligence systems. Their work involves identifying potential threats such as bias, security vulnerabilities, ethical concerns, and compliance issues that could arise from using AI technologies. They collaborate with data scientists, engineers, and compliance teams to develop risk mitigation strategies and ensure that AI systems operate safely, ethically, and in accordance with relevant regulations.

What cities near Romeoville, IL are hiring for Ai Risk Analyst jobs?

Cities near Romeoville, IL with the most Ai Risk Analyst job openings:

Infographic showing various Ai Risk Analyst job openings in Romeoville, IL as of August 2026, with employment types broken down into 75% Full Time, 21% Part Time, and 4% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution, with an average salary of $85,861 per year, or $41.3 per hour.

Director of Payments & Risk

Coinme

Chicago, IL • On-site

Full-time

Posted 17 days ago


Job description

At Coinme, we're redefining access to financial services in a digital world. By combining the cutting-edge power of blockchain technology with everyday simplicity, we make digital currencies accessible and usable for all.

As the world's largest network of cryptocurrency kiosks with over 40,000 locations nationwide, we're breaking down barriers to crypto adoption through our seamless mobile app, secure digital wallet, and DeFi integrations. Beyond our consumer offerings, we're also the infrastructure powering the crypto revolution for businesses.

Through our enterprise Crypto-as-a-Service (CaaS) platform, we enable businesses to launch crypto capabilities in weeks, not months. Our modular, API-first infrastructure provides everything from KYC and payment processing to liquidity and custody solutions—all fully licensed and compliant.

We're big enough to lead the charge in decentralized finance but small enough that your ideas will make waves. Every role at Coinme contributes to building a financial future where everyone has the tools to thrive. At Coinme, your growth fuels our mission. Together, we RISE.

About the Role

Coinme's Payments & Risk team keeps transactions safe, disputes defensible, and fraud controls sharp as we scale across consumer and platform channels. The Director of Payments & Risk owns that mission end to end: the fraud defense strategy, the AI-augmented operation that executes it, and the team that runs it.

This is a player-coach role. You set the defense architecture across fraud vendors, card processors, and banking partners, working closely with internal stakeholders such as Compliance, Product and Engineering and you keep enough hands-on depth to read raw logs and question what a rule actually did. You build and govern AI-assisted workflows that carry much of the operational load, and you develop the analysts and scientists who operate them. Decisions here are made on evidence, at speed, and must survive audit, and the function you build must not depend on any single person, including you. You own the economics of risk: losses, recoveries, and the customer friction in between.

What You'll Do
  • Own the fraud risk strategy and the end-to-end defense architecture across the payments stack: vendor risk engines, internal controls, processor-level gates, and partner-bank requirements, with a current map of which system makes which decision.
  • Run the detection portfolio as a measured system: rules, thresholds, models, and velocity limits tuned against quantified false-positive versus fraud-capture tradeoffs, with disciplined change control and post-change monitoring.
  • Own the chargeback and dispute program economics: representing strategy, pre-dispute deflection signals (Ethoca, Verifi RDR, Compelling Evidence 3.0), win-rate and net-recovery reporting, and card-network monitoring standing.
  • Lead fraud investigations and incident response with evidence-first discipline: reconstruct the decision trail across vendor logs, application telemetry, and processor responses before assigning a disposition; distinguish system defects from legitimate controls; defend legitimate declines against pressure to override; and turn incidents into durable fixes.
  • Design and govern AI-native risk operations: agentic workflows for queue triage, decline forensics, fraud-ring detection, chargeback evidence assembly, and scheduled monitoring, with governance to match (QA gates before anything ships externally, human-in-the-loop checkpoints on account-level actions, auditable reasoning trails, and explicit boundaries on what automation may decide).
  • Build and develop the team: hire, coach, and grow risk analysts and scientists, and train them to operate and extend the AI-assisted workflows, with documentation and runbooks treated as first-class deliverables.
  • Drive root-cause fixes across the entire payment flow and customer journey: when a risk gap lives in another team's system (compliance workflows, account lifecycle, internal tooling), own the influence campaign to fix it there instead of compensating downstream, and partner closely with compliance on the fraud/AML seam.
  • Manage the vendor and partner ecosystem at both levels: hands-on (rules, integrations, data quality) and commercial (SLAs, escalation paths, roadmap influence), and coordinate risk posture with processors, sponsor banks, and platform partners.
  • With a strong bias for action, report to executives on key risk mitigating actions to reduce risk exposure and loss, performance and risk metrics , with the ability to go beyond headline fraud rates: loss by channel, decline precision and false-positive cost, dispute win rates, automation coverage, and time-to-disposition, connecting risk decisions to profitability.
What Success Looks Like (first 6 to 12 months)
  • You own the full fraud defense architecture with no or minimal regression in loss rate, chargeback ratio, or card-network monitoring standing through the transition.
  • Clearly demonstrating strong decision making capability, especially in a crisis event, where time and rapid response is critical.
  • The AI-assisted risk operation runs as a team-owned product: documented, version-controlled, monitored, and extended by the team, with no single-person dependencies.
  • The team is hired, ramped, and closing investigations independently within SLA, each with defensible written rationale.
  • Strong focus on fixing any identified process gaps.Vendor and processor relationships run on standing commercial reviews: SLAs, escalation paths, and roadmap input.
  • Executive reporting is standing and quantified, and it connects risk decisions to profitability.
What You Bring (Must-Have)
  • Experience: 8+ years in payments risk, fraud, or dispute operations within financial services or cryptocurrency, including 3+ years leading a risk, fraud, or trust and safety function, ideally at a crypto exchange or on/off-ramp.
  • Payments and fraud depth: Card-rail mechanics (authorization and decline flows), chargeback and representment economics, Visa and Mastercard dispute rules and card-network monitoring programs, working knowledge of ACH and real-time rails, and fluency in crypto-side risk (wallet behavior, on-chain flows, cash-out typologies).
  • Platform fluency: Extensive hands-on administration of modern fraud prevention platforms (Sardine, SEON, Sift, Kount, Forter, or similar), including rule authoring, shadow-versus-live testing, and the instinct to reverse-engineer what a rule actually does rather than trust its label.
  • Data fluency: Strong SQL and comfort in log and observability platforms and analytics tooling; you answer your own questions without waiting on an analyst.
  • AI-native leadership: You have built or governed AI-assisted operational workflows and can speak concretely about what you automated, what guardrails you set, and what you deliberately kept human. Aptitude is assessed in a working session.
  • Institution building: You document, cross-train, and design systems that outlive your tenure; the functions you leave keep running without you.
  • Influence: You change processes you don't own, fixing root causes in other teams' systems rather than building permanent workarounds.
  • People leadership: You have hired, developed, and retained analysts, and you can lead a team through AI-driven change in how the work itself gets done.
  • Judgment: Evidence discipline over convenient narratives, conservative and defensible metrics over optimistic ones, protection of good customers weighed as seriously as fraud losses, and clear communication to both technical and executive audiences.
Nice to Have
  • Direct experience with the Sardine platform and/or card processor integrations (TabaPay or similar).
  • Threat-informed defense frameworks (MITRE ATT&CK, AADAPT, F3) applied to fraud.
  • Blockchain analytics tooling (TRM Labs, Chainalysis, Elliptic) and wallet-clustering investigations.
  • BSA/AML and SAR familiarity, including SAR-aware evidence handling and partnering with compliance on account lock and reactivation policy.
  • Experience building with LLM agent frameworks (Claude Code, agent SDKs) or workflow-automation platforms.
  • Modern data-stack familiarity: dbt, warehouse modeling, product analytics.
  • Certifications (CFE, CAMS, FRM) or an advanced degree in a relevant field.
How We Work

We measure before we act, count wins only when they are confirmed, and keep an audit trail for every change. We protect good customers as fiercely as we stop fraud, and we treat AI tooling as core to the job, not a novelty. If that is how you already think about risk, you'll fit right in.

Check out our AI Usage Guidelines to understand how we approach AI tools during the hiring process.