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Gaming Fraud Risk Analyst Jobs in Toronto, ON (NOW HIRING)

Chad Management Group

VP credit Risk & Analytics

Toronto, ON · On-site

CA$160K - CA$180K/yr

VP Credit Risk & Analytics Cambridge ON With over $1Billion in loans funded, our client has helped ... Acquisitions, Adjudication, Credit Limit Assignment, Portfolio Management, Collections, Fraud, Loss ...

Td

Data Scientist II

Markham, ON · On-site

CA$81K - CA$115K/yr

You would manage evolving fraud threats while taking into consideration TD risk appetite, Customer and operational experience. With strong technical, analytics background you would join the team to ...

Loop

Head of Risk

Toronto, ON · On-site

$120 - $140/hr

Translate emerging fraud and money laundering patterns into rule, policy, and product changes ... Sharp analytical thinking and clear communication, paired with sound judgment and high ethical ...

Rakuten Kobo

Fraud Lead (12-month contract)

Toronto, ON · On-site +1

The Role: Rakuten Kobo Inc. is looking for a Fraud Lead (12 month contract) to join our Risk ... Strong analytical skills with the ability to identify fraud trends and patterns * Familiarity with ...

Scotiabank

Director, Major Investigations

Toronto, ON · On-site

$100 - $130/hr

Apply investigative methodology focusing on the tactical use of gathered intelligence through data analytics and network analysis to identify organized criminal groups and emerging fraud risk trends ...

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Gaming Fraud Risk Analyst information

What does a gaming fraud risk analyst do?

A Gaming Fraud Risk Analyst is responsible for identifying, investigating, and preventing fraudulent activities within online or offline gaming platforms. They analyze player behavior, monitor transactions, and use various tools and data analytics to detect suspicious activities such as account takeovers, payment fraud, or cheating. Their role helps gaming companies maintain fair play, protect user accounts, and comply with legal regulations. They also collaborate with other teams to improve fraud prevention strategies and minimize financial losses.

What are the key skills and qualifications needed to thrive as a gaming fraud risk analyst, and why are they important?

To thrive as a Gaming Fraud Risk Analyst, you need strong analytical skills, attention to detail, and a solid understanding of gaming industry regulations, often supported by a degree in finance, business, or a related field. Familiarity with fraud detection software, data analysis tools like SQL or Python, and knowledge of anti-money laundering (AML) systems are typically required. Critical thinking, problem-solving, and effective communication are valuable soft skills for investigating suspicious activity and collaborating with other departments. These skills are essential to accurately identify fraudulent behavior, minimize risks, and protect both the company and its players.

What are some common challenges faced by gaming fraud risk analysts in the gaming industry?

Gaming Fraud Risk Analysts often encounter challenges such as staying ahead of rapidly evolving fraud techniques and distinguishing between legitimate user behavior and suspicious activity. They must analyze large volumes of transactional and behavioral data, which requires attention to detail and proficiency with analytical tools. Collaboration with engineering, customer support, and compliance teams is essential to implement effective anti-fraud measures and respond quickly to emerging threats. Continuous learning and adaptability are key, as fraud methods and gaming technologies frequently change.
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Gaming Fraud Risk Analyst jobs near you
Infographic showing various Gaming Fraud Risk Analyst job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

VP credit Risk & Analytics

Chad Management Group

Toronto, ON • On-site

CA$160K - CA$180K/yr

Full-time

Re-posted 16 days ago

Job description

VP Credit Risk & Analytics

Cambridge ON

With over $1Billion in loans funded, our client has helped hard-working Canadians with personalized money solutions with more flexibility than traditional banks across both its retail and digital channels. They are a member of the Canadian Consumer Finance Association, fully licensed lender with 110+ branches across Ontario. The company believes their customers deserve clear, understandable loan terms and therefore encourage fair and fully disclosed lending practices. The company is on a National growth path, working to digitize the end to end consumer lending experience.

About The Role:

The successful candidates will play an instrumental role assisting with the development of the company's strategy to enhance its Credit Scoring capabilities and exponentially grow its consumer loan portfolio, in branch and digital.

This role will support the development, enhancement and monitoring of all credit scores used in the entire lifecycle of credit: Acquisitions, Adjudication, Credit Limit Assignment, Portfolio Management, Collections, Fraud, Loss Forecasting.

The successful candidate will bring strong statistical knowledge and experience in a credit risk environment with a proven track record of working with other business leaders from across the organization to drive analytically based strategies.

Qualifications:

  • 5+ years of experience within consumer lending environment
  • Experience building predictive models, regression modeling, credit modelling for auto adjudication, decision trees, logistics regression, etc.
  • Experience with R, Matlab, Python or Base SAS.
  • Demonstrated understanding of credit scores and, their use in business strategies, post implementation use, and monitoring
  • Knowledge of automated decision engines (helped automating decision engines for different clients)
  • Strong project management and communication skills
  • Proven analytical and conceptual thinker who can adapt to a rapidly changing environment
  • Demonstrated ability in working within team and collaborating with multiple stakeholders to understand issues and solve problems
  • Ability to distill and communicate complex analytic recommendations to both technical and non-technical stakeholders, both orally and in written presentations
  • Educational backgrounds in Applied Statistics, Computer Science, Risk Management, Financial Engineering, Statistical Modelling