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Fraud Analytics Jobs in Toronto, ON (NOW HIRING)

Lyft

Fraud & Risk Analyst

Toronto, ON

The PII Analytics team is one of the most critical teams that helps protect Lyft and enables the ... The team is fast-paced, high-energy, and meticulous in diagnosing emerging fraud patterns and ...

Scotiabank

Fraud Business Analyst

Toronto, ON

The role works closely with Fraud Program Management, Fraud Operations, Analytics, Technology, business lines, and control partners to strengthen fraud prevention, detection, monitoring, and ...

Scotiabank

Manager, Fraud Deterrence

Toronto, ON · On-site

This is achieved by managing a team of Senior Fraud Analysts and Assistant Managers who use a variety of tools to identify and review suspected cheque fraud, kiting activities, suspected payment ...

CIBC

Analyst, Fraud Controls

Toronto, ON · Hybrid

To learn more about CIBC, please visit CIBC.com What you'll be doing Analyst, Fraud Controls will be responsible for identifying, analyzing and conducting investigations of client transaction ...

CIBC US

Analyst, Fraud Controls

Toronto, ON · Hybrid

To learn more about CIBC, please visit CIBC.com What you'll be doing Analyst, Fraud Controls will be responsible for identifying, analyzing and conducting investigations of client transaction ...

Stripe

Data Scientist, Fraud

Toronto, ON

We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime ...

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Fraud Analytics information

See Toronto, ON salary details

$25.8K

$89.6K

$141.2K

How much do fraud analytics jobs pay per year?

As of Sep 1, 2026, the average yearly pay for fraud analytics in Toronto, ON is $89,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,712.00 and $115,475.00 per year, depending on experience, location, and employer.

What is fraud analytics?

Fraud analytics is the process of using data analysis, statistical methods, and machine learning techniques to detect, prevent, and investigate fraudulent activities within an organization. Professionals in this field analyze large sets of transactional and behavioral data to identify patterns and anomalies that may indicate fraud. Fraud analytics is commonly used in industries such as banking, insurance, retail, and e-commerce to minimize financial losses and protect customers. The role often involves working with specialized software and collaborating with other teams to implement effective anti-fraud strategies.

How does a fraud analytics professional typically collaborate with other departments within an organization?

Fraud Analytics professionals frequently work cross-functionally, partnering with teams such as IT, compliance, risk management, and customer service. They analyze data to identify suspicious activities and then communicate findings to relevant stakeholders, often participating in investigations or recommending process improvements. Effective collaboration ensures that fraud detection strategies stay up-to-date and align with broader organizational goals, making strong communication skills and teamwork essential for success in this role.

What are the key skills and qualifications needed to thrive as a fraud analytics professional, and why are they important?

To thrive in Fraud Analytics, you need strong analytical abilities, proficiency in statistics, and experience with data analysis, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with data mining tools, SQL, Python, machine learning platforms, and certifications like Certified Fraud Examiner (CFE) are typically required. Attention to detail, critical thinking, and effective communication are essential soft skills for interpreting data patterns and presenting findings to stakeholders. These skills are crucial for detecting fraudulent activities, minimizing financial risks, and supporting organizational integrity.

What is the difference between Fraud Analytics vs Fraud Prevention Specialist?

AspectFraud AnalyticsFraud Prevention Specialist
Primary FocusAnalyzing data to detect and predict fraudulent activitiesImplementing strategies and actions to prevent fraud
Skills & CertificationsData analysis, statistical tools, SQL, certifications like Certified Fraud Examiner (CFE)Customer service, risk management, fraud detection techniques, certifications like CFE
Work EnvironmentData analysis teams, financial institutions, tech companiesCustomer support centers, financial institutions, retail
GoalsIdentify patterns, develop models, improve detection accuracyReduce fraud incidents, enhance prevention measures

While both roles aim to combat fraud, Fraud Analytics focuses on analyzing data to identify and predict fraudulent activities, whereas Fraud Prevention Specialists implement measures to prevent fraud from occurring. Both roles often collaborate but serve different functions within fraud management strategies.

How do I become a fraud analyst?

To become a fraud analyst, typically a bachelor's degree in finance, accounting, or a related field is required. Relevant skills include data analysis, knowledge of fraud detection tools, and familiarity with databases and reporting software; certifications like Certified Fraud Examiner (CFE) can enhance prospects. Gaining experience through internships or entry-level roles in finance or security is also beneficial.

How much does a fraud analyst get paid?

A fraud analyst's salary typically ranges from $50,000 to $80,000 annually, depending on experience, location, and industry. Entry-level positions may start lower, while experienced analysts with certifications or specialized skills can earn higher salaries. Many roles also include benefits such as bonuses and professional development opportunities.

Is fraud analysis a good career?

Fraud analysis is a growing field within risk management that involves detecting and preventing fraudulent activities using data analysis and investigative skills. It offers opportunities for advancement, requires knowledge of analytics tools, and often involves working in financial or e-commerce environments. The role can be stable and rewarding for those interested in security and data-driven decision making.

What does a fraud analytics do?

A fraud analyst uses data analysis techniques to detect and prevent fraudulent activities within financial transactions or business operations. They analyze large datasets, identify patterns of suspicious behavior, and implement strategies to reduce fraud risk, often using tools like SQL, Excel, or specialized fraud detection software. Strong analytical skills and knowledge of fraud schemes are essential for this role.

What are the most commonly searched types of Fraud Analytics jobs in Toronto, ON?

The most popular types of Fraud Analytics jobs in Toronto, ON are:

What are popular job titles related to Fraud Analytics jobs in Toronto, ON?

For Fraud Analytics jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Fraud Analytics jobs in Toronto, ON look for?

The top searched job categories for Fraud Analytics jobs in Toronto, ON are:

Fraud Analytics jobs near you
Infographic showing various Fraud Analytics job openings in Toronto, ON as of August 2026, with employment types broken down into 1% Internship, 93% Full Time, 4% Part Time, and 2% Contract. Highlights an 80% Physical, 7% Hybrid, and 13% Remote job distribution, with an average salary of $89,560 per year, or $43.1 per hour.

Senior/Lead Risk Analyst, Payment fraud

Snaplii

Toronto, ON • On-site

$150K - $200K/yr

Full-time

Re-posted yesterday

Job description

Location: Toronto, Canada / On-site

Department: Risk & Payments

Compensation: $150K-$200K

About the Role
We are seeking a strategic and data-driven fraud and risk leader to join our Risk & Payments team. 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.

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

  • Experience working with variety of payment methods in multi-currency environment ideally in e-commerce or related industry.

  • 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.

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

  • 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.

Why Join Us
About Snaplii
Snaplii is one of Canada's fastest-growing fintech platforms, transforming how people pay, save, and earn rewards. With over $100M in annual transaction volume and 250,000+ users across North America, we deliver unmatched utility and loyalty through a single seamless app.

We've ranked as high as #5 on the Apple App Store during peak shopping seasons, and consistently remain in the Top 80-driven by a highly engaged, high-retention user base. As the most payment-flexible platform in the space, Snaplii supports a wide range of digital payment methods and partners with 400+ leading brands, including Walmart, Amazon, and Esso.

Our platform is fully built and maintained in-house-engineered to handle complex payment flows, scale with demand, and support a growing suite of financial products. We're actively expanding into new digital finance offerings to help users create, manage, and grow value in their everyday lives.

Join us as we shape the future of everyday spending.

Employment Type: FULL_TIME

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