Senior Data Scientist - Risk
New
CanadaFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine LearningSnowflakeRisk Managementdbt
Requirements
- 5+ years of experience in Data Science, Decision Science, or a similar analytical role.
- Experience in risk, fraud, trust & safety, AML, compliance, or related domains is strongly preferred.
- Strong proficiency in SQL and Python for data analysis and modeling.
- Experience with statistical methods, experimentation, causal inference, regression, classification, or decision modeling.
- Ability to apply machine learning techniques selectively to improve signal detection and decision quality.
- Strong experience working with modern data stacks such as Snowflake, dbt, or similar tools.
- Proven ability to translate complex analysis into clear business and product recommendations.
- Strong communication skills with experience influencing cross-functional stakeholders.
- Ability to thrive in ambiguous, fast-moving environments with evolving priorities.
- Strong ownership mindset with excellent problem-solving and critical thinking skills.
- Interest or experience in fintech, crypto, payments, or regulated industries is an asset.
Responsibilities
- Partner with engineering teams to define the architecture and technical strategy for risk systems, data infrastructure, and decisioning frameworks.
- Collaborate with Risk, Product, Security, Compliance, and Operations teams to define risk metrics, success criteria, and analytical frameworks.
- Analyze fraud, scam, and abuse patterns across crypto and fiat platforms to identify emerging risks and vulnerabilities.
- Build and maintain dashboards and reporting systems tracking fraud loss, false positives, customer friction, and operational efficiency.
- Design and improve data instrumentation, risk controls, and decisioning systems supporting fraud prevention workflows.
- Conduct deep-dive investigations into incidents, anomalies, and evolving threat patterns to generate actionable insights.
- Evaluate risk rules and controls using statistical methods and selective machine learning techniques to improve decision quality.
- Communicate findings and recommendations clearly to senior stakeholders and cross-functional partners.
- Help establish data standards, analytical frameworks, and best practices within the risk organization.
- Support the translation of analytical insights into product, engineering, and operational improvements.
View Full Description & ApplyYou'll be redirected to the employer's site
