Lead Risk Analyst, Payment Fraud

Vaco by Highspring; Toronto; On-site; CAD 110,000 - 160,000; Full time

Job summary

Snaplli is seeking a Fraud and Risk Lead to own the full lifecycle of financial risk strategy development and implementation, from identifying opportunities to designing, testing, launching, and monitoring post-production performance.

You will detect, investigate, and track fraudulent activities, analyze datasets to produce root-cause analyses, and collaborate with engineers and product managers to deploy fraud prevention solutions that balance growth with strong controls.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Statistics, Finance, or related field.
• 5+ years of professional experience, with 3+ years in fraud and 1 year in payments.
• Experience with multi-currency payments and e-commerce.
• Experience building fraud detection models and user behavior scoring.
• Strong SQL skills; Python a plus.
• Experience deploying models in production.
• Experience integrating models into risk systems.
• Strong problem-solving and analytical thinking.
• Mandarin Chinese is a plus.

Responsibilities

• Lead the full lifecycle of financial risk strategy development and implementation.
• Detect, investigate, and track fraudulent or suspicious activities.
• Analyze datasets to deliver reports and root-cause analyses on fraud and chargebacks.
• Collaborate with engineers and product managers to deploy fraud prevention solutions.
• Serve as the primary contact with payment processors and vendors.
• Handle transactions across multiple currencies (USD, CAD, and others).

Skills

SQL

Python

Data Modeling

Fraud Analysis

ML Frameworks

Analytical Thinking

Communication

Education

Bachelor's degree

Tools

Sklearn

XGBoost

LightGBM

Job description

• About the OpportunityLead the full lifecycle of financial risk strategy development and implementation—from identifying opportunities to designing, testing, launching, and monitoring post-production performance.
• Detect, investigate, and track fraudulent or suspicious activities, including identifying and quantifying key trends impacting fraud and payment behaviors.
• Analyze both internal and external datasets to deliver detailed reports and root-cause analyses on fraud incidents and chargebacks.
• Collaborate closely with engineers and product managers to implement fraud prevention solutions that support business growth while maintaining strong risk controls.
• Serve as the primary point of contact with payment processors and vendors, leveraging strong communication skills to manage relationships, align on risk strategies, and navigate industry terminology.
• Experienced in handling transactions across multiple currencies, including USD, CAD, and others.
• About You:The ideal candidate is a reliable and resilient team player who combines strong business judgment, technical expertise, and advanced analytical skills to support Snaplli’s rapid growth.
• Minimum of 5 years of professional experience, including at least 3 years in a fraud-related role and 1 year within the payments industry.
• Experience working with multiple payment methods in multi-currency environments, preferably in e-commerce or similar industries.
• Demonstrated ability to investigate and detect fraudulent activity, with hands-on experience conducting transaction reviews and fraud case investigations.
• Strong background in data modeling (3+ years), including building fraud detection models, user behavior scoring systems, and transaction anomaly detection models. Experience with feature engineering, model training, evaluation, and deployment is required.
• Experience integrating models into risk systems to support automated, model-driven fraud prevention processes.
• Proficiency with machine learning frameworks (Python or R using tools such as Sklearn, XGBoost, or LightGBM) and experience deploying models in production environments.
• Strong SQL skills (required) with the ability to independently query and analyze large datasets; Python experience is a plus.
• Previous experience in roles such as Fraud Analyst, Risk Analyst, Operations Specialist, Data Scientist, or Product Manager. A bachelor’s degree in Engineering, Computer Science, Statistics, Finance, or a related analytical or technical discipline is preferred.
• Strong problem-solving and analytical thinking abilities, including the capacity to think from a fraudster’s perspective to anticipate and mitigate risks.
• Mandarin Chinese proficiency is considered an asset but is not required.