Senior Data Scientist - Risk
Skills
About the Role
You will define how risk is measured and managed, working closely with engineering and business partners to build reporting, decisioning systems, and instrumentation. You will analyze fraud, scam, and abuse patterns, conduct deep-dive investigations, evaluate and iterate on risk rules, apply statistical methods and selective machine learning where useful, and communicate insights to senior stakeholders. You will also help establish data standards, analytical methods, and decision-making practices for risk operations.
Requirements
- 5+ years of experience as a Data Scientist, Decision Science or in a similar analytical role
- Experience with fraud, risk, trust and safety, AML, or compliance analytics
- Strong proficiency in SQL and Python
- Experience performing deep analytical work and ML techniques related to regression, classification, experiment design, causal inference, or decision analysis
- Strong product and business judgment with ability to connect analysis to customer and risk outcomes
- Experience working with modern cloud data warehouses and tooling such as Snowflake and dbt
- Outstanding communication skills and ability to translate complex analysis into clear business recommendations
- Proven ability to work in ambiguous, fast-moving environments
- Strong sense of ownership and ability to challenge assumptions constructively
- Experience partnering closely with cross-functional stakeholders to influence decisions
- Good judgment when tailoring the analytical toolkit to the problem at hand
- Interest in Bitcoin and familiarity with fintech, payments, crypto, or other regulated industries
- Fluency in English
Responsibilities
- Define architecture and technical strategy for internal risk systems and tooling
- Define risk metrics, success criteria, and decision frameworks with stakeholders
- Analyze fraud, scam, and abuse patterns across crypto and fiat products
- Build and maintain reporting tracking fraud loss, false positives, customer friction, operational efficiency, and control performance
- Design and architect data, instrumentation, and decisioning systems for risk operations and fraud prevention
- Evaluate and iterate on risk rules and controls using rigorous analysis
- Apply statistical methods and selective machine learning to improve decision quality, efficiency, or signal detection
- Conduct deep-dive investigations into incidents, trends, and emerging threats
- Communicate insights clearly and persuasively to senior stakeholders
- Establish data standards, analytical methods, and decision-making practices within the Risk team
Benefits
- Stock options (equity)
- Yearly salary assessments
- Comprehensive health and dental coverage including health and wellness spending accounts
- Remote work from anywhere in Canada with optional office access in Montreal and Toronto
- CAD 2,000 annual budget for courses, certifications, and training
- 20 days of vacation per year plus a CAD 1,000 bonus if you use all vacation
- Parental leave top-up to 100% of salary for 18 weeks
- Quarterly team-specific or company-wide offsite