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Data Scientist Fraud Detection Jobs in Toronto, ON

Manulife

Associate Data Scientist

Toronto, ON · Hybrid

CA$80.63K - CA$134.38K/yr

Support the development and enhancement of fraud detection and risk analytics models, including ... Partner with senior data scientists, engineers, and business stakeholders to understand ...

Manulife

Senior Data Scientist

Toronto, ON · Hybrid

Lead end to end development of fraud detection and risk analytics models, including probabilistic ... D. degree in Computer Science, Data Science, Statistics, Engineering, Physics, or a related ...

Hibernian General Insurance

Data Scientist

Toronto, ON

CA$80K - CA$120K/yr

As a Data Scientist on the Fraud Data Science team , you'll work closely with a wide range of ... You'll contribute to highimpact initiatives focused on fraud detection, using machinelearningbased ...

Hibernian General Insurance

Data Scientist

Markham, ON

CA$80K - CA$120K/yr

As a Data Scientist on the Fraud Data Science team , you'll work closely with a wide range of ... You'll contribute to highimpact initiatives focused on fraud detection, using machinelearningbased ...

Finlink Group

Senior Fraud Strategy Lead

Brampton, ON

Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers ... Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or ...

Finlink Group

Senior Fraud Strategy Lead

Toronto, ON

Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers ... Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or ...

Finlink Group

Senior Fraud Strategy Lead

Toronto, ON

Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers ... Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or ...

Finlink Group

Senior Fraud Strategy Lead

Toronto, ON

Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers ... Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or ...

Royal Bank of Canada

Data Scientist

Toronto, ON

... fraud detection and AML, voice assistants in customer service, to algorithmic trading in capital ... You will work with model developers (data scientists, researchers, engineers) and business ...

Finlink Group

Senior Fraud Strategy Lead

Brampton, ON

Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers ... Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or ...

Finlink Group

Senior Fraud Strategy Lead

Toronto, ON

Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers ... Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or ...

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Data Scientist Fraud Detection information

What are the key skills and qualifications needed to thrive as a Data Scientist in Fraud Detection, and why are they important?

To thrive as a Data Scientist in Fraud Detection, you need a strong background in statistics, machine learning, and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with big data tools (e.g., Hadoop, Spark), and knowledge of fraud detection platforms are essential. Strong problem-solving abilities, attention to detail, and effective communication skills set candidates apart in this field. These skills and qualities are crucial for identifying fraudulent activities quickly and accurately, minimizing financial losses, and supporting organizational security.

How does a Data Scientist in Fraud Detection typically collaborate with other teams to develop effective solutions?

As a Data Scientist in Fraud Detection, you will regularly collaborate with cross-functional teams such as fraud analysts, software engineers, and product managers. Working closely with fraud analysts helps you understand emerging fraud patterns, while partnering with engineers ensures your models are effectively integrated into real-time systems. You may also coordinate with compliance and legal teams to ensure solutions meet regulatory requirements. This collaborative approach not only improves the accuracy and impact of fraud detection models but also fosters a dynamic, supportive work environment.

What does a Data Scientist in Fraud Detection do?

A Data Scientist in Fraud Detection analyzes large datasets to identify patterns and anomalies that could indicate fraudulent activities. They use machine learning algorithms, statistical models, and data mining techniques to detect and prevent fraud in areas like banking, insurance, and e-commerce. Their work helps organizations proactively combat fraud by developing predictive models and automated systems that flag suspicious transactions. Additionally, they often collaborate with other departments to refine detection strategies and ensure compliance with regulations.

What is the difference between Data Scientist Fraud Detection vs Data Analyst Fraud Detection?

AspectData Scientist Fraud DetectionData Analyst Fraud Detection
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL
Work EnvironmentDeveloping models, advanced analytics, machine learning tasksData cleaning, reporting, basic analysis
Employer & Industry UsageFinancial institutions, e-commerce, insurance

Data Scientist Fraud Detection focuses on building predictive models and applying machine learning techniques to identify fraud patterns. Data Analysts Fraud Detection primarily perform data cleaning, reporting, and basic analysis to support fraud detection efforts. While both roles work in similar industries, Data Scientists handle more complex modeling, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Data Scientist Fraud Detection jobs in Toronto, ON? For Data Scientist Fraud Detection jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Data Scientist Fraud Detection jobs in Toronto, ON look for? The top searched job categories for Data Scientist Fraud Detection jobs in Toronto, ON are:
Data Scientist Fraud Detection jobs near you
Infographic showing various Data Scientist Fraud Detection job openings in Toronto, ON as of May 2026, with employment types broken down into 76% Full Time, 8% Part Time, and 16% Contract. Highlights an 83% Physical, 7% Hybrid, and 10% Remote job distribution.

Associate Data Scientist - User Fraud

Spotify

Toronto, ON • On-site

CA$61.47K - CA$87.82K/yr

Other

Medical, Dental, Retirement, PTO

Posted 26 days ago

Job description

We're looking for a Data Scientist to join the band. You'll help us expand detection and mitigation methods against abuse across all audio verticals on our platform. The team's goal is to ensure a fraud-free experience for users and creators by employing advanced technology and evolving strategies to maintain fair engagement and accuracy.

As part of the team, you'll contribute to our data-driven approach, protecting the platform's integrity from issues like account abuse and artificial manipulation. Your work will directly impact how billions of fans connect with millions of artists and creators, and how the world experiences content.

You'll work with a team of data scientists and machine learning engineers to detect and prevent abuse on our platform. You'll help us investigate anomalous trends, discover new ways to leverage data for improved detection methods, and identify unwanted behavior on the platform. We are a fast-paced team passionate about high-impact projects, and we prioritize continuous learning and skill development. You will have the freedom to refine your skills and working methods.


 
What You'll Do

  • Investigate evolving fraud trends and consumption habits to enhance detection capabilities.

  • Apply your expertise in quantitative analysis, data mining, and data presentation to help automate, optimize and understand key business problems and solutions.

  • Build data and tooling to empower operational and exploratory data analysis while optimizing for speed, accuracy, and quality.

  • Work closely with cross-functional teams of data and backend engineers, and product managers.

  • Partner with a broad range of stakeholders across music, podcasts and audiobooks to consistently uphold platform integrity.

Who You Are

  • A Bachelor's degree in Data Science, CS, or another quantitative field.

  • 1+ years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines.

  • Deep understanding of data with expertise in data manipulation and design (SQL) and experience in Python.

  • Strong analytical skills, with the ability to turn data into actionable insights and recommendations.

  • Strong problem-solving skills, intellectual curiosity, and a proactive approach to identifying new opportunities for fraud detection.

  • A continuous learner, excited by new technologies and able to pick up new tools and frameworks quickly.

Where You'll Be
This role is based in Toronto.
 
We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. 
The Canada base range for this position is $61,472 - $87,817 CAD plus equity. Benefits available for this position include extended health and dental coverage, retirement savings plans, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and other benefits in accordance with Canadian employment standards. These ranges and benefits may be modified in the future.
 
 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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