Fraud Detection Analyst

leading-edge; Hamilton; On-site; CAD 65,000 - 90,000; Full time

Job summary

leading-edge is seeking a highly skilled Fraud Detection Analyst to join our Risk Management team. You will analyze large datasets to identify patterns and anomalies, leveraging Excel, SQL, and statistical tools to detect fraud risks and prevent losses.

The role involves investigating suspicious activity, assessing risk for new and existing customers, and reporting trends to management while collaborating with Compliance, Risk, and Customer Service to enhance processes.

Qualifications

• Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science or Engineering.
• 2–3 years of experience in fraud detection, risk management, or a related field.
• Proficiency in data analytics tools (Excel, SQL) and statistical software (R, Python).

Responsibilities

• Data Analysis: Analyze large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity.
• Fraud Detection: Use data analytics and machine learning techniques to detect and prevent fraudulent transactions.
• Risk Assessment: Assess the risk of fraud for new and existing customers and develop mitigation strategies.
• Investigation: Investigate suspicious transactions and collaborate with internal stakeholders to resolve cases.
• Reporting: Provide regular reports to management on fraud trends, risks, and detection results.
• Process Improvement: Continuously evaluate and improve fraud detection processes and procedures.
• Collaboration: Work with Risk Management, Compliance, and Customer Service.

Skills

Data analysis

Analytical skills

Communication skills

Education

Bachelor's degree in a quantitative field

Tools

Excel

SQL

R

Python

Job description

Job Summary

We are seeking a highly skilled and detail-oriented Fraud Detection Analyst to join our Risk Management team. The successful candidate will be responsible for analyzing data and identifying potential fraud risks to prevent financial losses and protect our customers' assets.

Key Responsibilities

1. Data Analysis: Analyze large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity.
2. Fraud Detection: Use data analytics and machine learning techniques to detect and prevent fraudulent transactions, such as credit card fraud, identity theft, and account takeover.
3. Risk Assessment: Assess the risk of fraud for new and existing customers, and develop strategies to mitigate those risks.
4. Investigation: Investigate suspicious transactions and activity, and collaborate with internal stakeholders to resolve cases.
5. Reporting: Provide regular reports to management on fraud trends, risks, and detection results.
6. Process Improvement: Continuously evaluate and improve fraud detection processes and procedures.
7. Collaboration: Work closely with cross-functional teams, including Risk Management, Compliance, and Customer Service.

Requirements

1. Education: Bachelor's degree in a quantitative field, such as Mathematics, Statistics, Computer Science, or Engineering.
2. Experience: Minimum 2-3 years of experience in fraud detection, risk management, or a related field.
3. Technical Skills: Proficiency in data analytics tools, such as Excel, SQL, and statistical software (e.g., R, Python).
4. Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret complex data.
5. Communication Skills: Excellent communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.