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Payment Risk Jobs in Toronto, ON (NOW HIRING)

About the Organization Payments and Risk Sub-orgs within Payments and Risk: Link and OCS, Payments Acceptance, Risk The Payments organization focuses on developing products and platforms that enable ...

Experience with AML detection systems, crypto or emerging payments risk, anomaly detection, behavioral modelling, or model governance. Mastercard is a merit-based, inclusive, equal opportunity ...

... resilience, and risk management * Build Capco's payments capabilities and thought leadership ... Experience working with payment service providers, fintechs, or payments ISVs * Exposure to ...

... payment finality to ensure accurate and resilient transaction processing * Partnering with Fraud, Security, Risk, Compliance, Operations, and Engineering teams to validate fraud controls ...

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Payment Risk information

What is the difference between Payment Risk vs Credit Analyst?

AspectPayment RiskCredit Analyst
Required CredentialsFinancial certifications, risk management trainingFinance, accounting degrees, certifications like CFA or CPA
Work EnvironmentFinancial institutions, risk management departmentsBanks, lending companies, corporate finance
Employer & Industry UsageUsed in risk assessment for payments and transactionsUsed in evaluating creditworthiness of individuals or companies

Payment Risk professionals focus on assessing the likelihood of payment defaults and managing risks related to transactions. Credit Analysts evaluate the creditworthiness of borrowers to determine loan eligibility. While both roles involve financial analysis and risk assessment, Payment Risk is more transaction-focused, whereas Credit Analysts concentrate on credit profiles and lending decisions.

What is a payment risk?

Payment risk refers to the potential for financial loss due to the failure of a payment to be completed or authorized, often caused by fraud, credit issues, or technical errors. Payment risk management involves assessing transaction data and using tools like fraud detection software to minimize losses and ensure secure payments.
Infographic showing various Payment Risk job openings in Toronto, ON as of September 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, and 3% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

Senior Fraud Strategy Lead - Multi-Currency Wallet

Toronto, ON โ€ข 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