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Ai Risk Analyst Jobs in Ontario (NOW HIRING)

Facilitate project qualitative risk assessments and Quantitative Cost Risk Analysis (QCRA) and ... and tools (AI-based); development of a mature risk culture on projects and within Hatch ...

Facilitate project qualitative risk assessments and Quantitative Cost Risk Analysis (QCRA) and ... and tools (AI-based); development of a mature risk culture on projects and within Hatch ...

... Analytics, Ops for data | infra | integration related to implementation Collaborate with teams to enforce responsible AI, model risk management, and AI governance Candidate Profile: Technical Skills ...

... Analytics, Ops for data | infra | integration related to implementation Collaborate with teams to enforce responsible AI, model risk management, and AI governance Candidate Profile: Technical Skills ...

AI Knowledge Operations Specialist

Toronto, ON · On-site

CA$90K - CA$130K/yr

Contribute knowledge quality data supporting AI quality and risk reporting. * Support investigation ... Strong research and analytical skills, with the ability to convert unstructured information into AI ...

Specifically modeling and advance math skills, working in SAS, AI, Tableau, Power BI, Databricks ... Risk Analytics, SAS Base Programming, SAS Enterprise, SAS Enterprise Guide, SAS Macros, SAS Program ...

Specifically modeling and advance math skills, working in SAS, AI, Tableau, Power BI, Databricks ... Risk Analytics, SAS Base Programming, SAS Enterprise, SAS Enterprise Guide, SAS Macros, SAS Program ...

Showing results 41-60

Ai Risk Analyst information

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 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.

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.

How much do AI risk analysts make?

AI risk analysts typically earn between $70,000 and $130,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in AI safety and risk management can earn higher salaries, often exceeding $150,000. The role often requires knowledge of AI systems, risk assessment, and relevant certifications.

How to become an AI risk analyst?

To become an AI risk analyst, candidates typically need a strong background in computer science, data analysis, or related fields, along with knowledge of AI systems and risk management principles. Relevant skills include programming, statistical analysis, and understanding of AI safety and ethics, often supported by certifications or advanced degrees. Experience with AI tools and risk assessment frameworks is also valuable.

What does an AI risk analyst do?

An AI risk analyst evaluates potential risks associated with artificial intelligence systems, including safety, ethical concerns, and unintended consequences. They analyze data, develop risk mitigation strategies, and often use tools like risk assessment frameworks to ensure AI deployment aligns with safety standards and regulations.

Will AI take over AI Risk Analyst jobs?

AI Risk Analysts evaluate and manage risks associated with artificial intelligence systems, a role that requires specialized knowledge of AI technologies, ethics, and safety protocols. While AI tools can assist in data analysis and risk assessment, human expertise remains essential for interpreting complex issues and making strategic decisions, so the job is unlikely to be fully automated in the near term.

What job categories do people searching Ai Risk Analyst jobs in Ontario look for?

The top searched job categories for Ai Risk Analyst jobs in Ontario are:

Infographic showing various Ai Risk Analyst job openings in Ontario as of September 2026, with employment types broken down into 1% Internship, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 67% Physical, 5% Hybrid, and 28% Remote job distribution.

Senior Fraud Strategy Lead - Multi-Currency Wallet

Toronto, ON • On-site

Snaplii
51 - 200 employees

$150K - $250K/yr

Full-time

Re-posted 24 days ago


Job description

At Snaplii, risk management isn't a "brake" on growth-it's the "supercharger" that enables our 300% explosive expansion. We aren't looking for analysts who just read reports; we want strategists who can reverse-engineer fraud loops and command AI to automatically sever risks.

About Snaplii

Snaplii is one of Canada's fastest-growing fintech platforms, with $100M+ in annual transaction volume and 350,000+ users across North America, Snaplii connects consumers with 500+ leading brands across everyday categories - enabling smarter spending with instant savings and rewards.

Today, Snaplii is evolving beyond a digital wallet into infrastructure for AI-native commerce - enabling secure, programmable transactions between users, brands, and AI agents.

AI drives demand. Snaplii executes the transaction.


About the Role
We are looking for a Risk Leader with deep fraud expertise and raw analytical horsepower. This role will shape and implement cutting-edge risk strategies that drive sustainable growth, minimize losses, and enhance the customer experience. The ideal candidate has direct experience in payment fraud detection and prevention, with the ability to spot fraudulent transactions and translate fraud patterns into scalable, data-driven solutions. This role requires a balance of hands-on fraud investigation, SQL-driven analytics, and collaboration with product and engineering teams to design and implement automated fraud controls.

Key Responsibilities

  • Lead the end-to-end development and execution of financial risk strategies-from opportunity identification to design, testing, launch, and post-production performance monitoring.

  • Identify, investigate and monitor fraudulent or anomalous activity, including isolating and quantifying specific trends driving changes to fraud and payment patterns.

  • Analyze internal and external data and produce authoritative reports and root-cause analysis on fraudulent activities and chargebacks.

  • Experienced in collaborating with engineers and product managers to successfully deploy fraud prevention solutions that balance growth with risk control.

  • Act as a liaison between the company and payment processors/vendors, with strong communication skills to speak the industry language, manage vendor relationships, and ensure effective alignment on fraud and risk management.

Qualifications

  • The ideal candidate is an accountable and resilient team-player who brings a combination of business instincts, technical skills and raw analytical horsepower necessary to support the rapid growth of Snaplli's business.

  • Minimum 5 years of professional work experience; Minimum 3 years in a fraud-related role; Minimum 1 year in the payments industry.

  • Experience working with various payment methods in multi-currency environments, ideally within e-commerce or related industries.

  • Proven ability to investigate and identify fraudulent activities, including hands-on experience with transaction reviews and fraud case analysis.

  • Strong data modeling skills (3+ years): hands-on experience building fraud detection models, user behaviour scoring systems, and transaction anomaly detection models, including feature engineering, model training, evaluation, and deployment.

  • Ability to integrate models with risk systems to enable automated, model-driven fraud prevention workflows.

  • Proficiency with machine learning frameworks (Python or R with Sklearn, XGBoost, LightGBM, etc.) and prior experience deploying models into production environments.

  • SQL proficiency (must-have) - able to independently query and analyze large datasets. Python (good-to-have).

  • Previous experience as a Fraud Analyst, Risk Analyst, Operations Specialist, Data Scientist, or Product Manager. Bachelor's degree in Engineering, Computer Science, Statistics, Finance, or a related analytical/technical field.

  • Strong problem-solving skills and reverse-engineering thinking, with the ability to anticipate and predict potential risks from a fraudster's perspective.

  • Proficiency in Mandarin Chinese is an asset but not required.

Why Join Us
  • Building AI-Native Payments

    • Powering how AI agents transact in the real world.

  • Explosive Growth

    • 300%+ revenue & TPV growth in 2025, with accelerating momentum into 2026.

  • Small Team, Massive Scale

    • <40 people. A lean & high-performance team where every decision moves revenue, risk, and user experience.

  • AI-First Engineering Culture

    • 90%+ of code is AI-assisted. Engineers focus on architecture and complex problems

  • Direct Access to the AI Frontier

    • Connect with leading AI companies in Silicon Valley, gaining first-hand exposure to cutting-edge advancements.

Employment Type: FULL_TIME