Senior Data Scientist - Risk
New
Work from anywhere in Canada, with optional access to our office spaces in Montreal and Toronto.Full-TimeSenior
Salary130,000 - 160,000 CAD per year
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Job Details
- Languages
- Fluency in English is required
- Experience
- 5+ years of experience as a Data Scientist, Decision Science or in a similar analytical role
- Required Skills
- PythonSQLMachine LearningSnowflakedbt
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 the ability to connect analytical work to customer outcomes, risk outcomes, and company priorities.
- Experience working with modern cloud data warehouses and tooling (i.e Snowflake, dbt, etc).
- Outstanding communication skills and the 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.
Responsibilities
- Partner with engineering to define the architecture and technical strategy for internal risk systems and tooling.
- Partner with Risk, Engineering, Security, Compliance, Product, and Operations to define risk metrics, success criteria, and decision frameworks.
- Analyze fraud, scam, and abuse patterns across crypto and fiat products.
- Build and maintain reporting that tracks fraud loss, false positives, customer friction, operational efficiency, and control performance.
- Help design and architect the data, instrumentation, and decisioning systems that power risk operations and fraud prevention workflows.
- Evaluate and iterate on risk rules and controls using rigorous analysis.
- Apply statistical methods and selective ML techniques where they materially improve decision quality, operational efficiency, or signal detection.
- Conduct deep-dive investigations into incidents, trends, and emerging threats.
- Communicate insights clearly and persuasively to senior stakeholders
- Help establish data standards, analytical methods, and decision-making practices within the Risk team
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