Senior Data Scientist, Shakepay

• 5+ years of experience as a Data Scientist or in a similar analytical role
• Strong proficiency in SQL and Python
• Experience with modern data stacks (e.g. Snowflake, dbt, Metabase, Preset)
• Experience performing deep analytical work (e.g. regression, classification, causal inference)
• Excellent communication skills with the ability to translate data into actionable insights and connect it to business objectives
• Proven ability to work in ambiguous, fast-moving environments (startup experience strongly preferred)
• Strong sense of ownership and ability to challenge assumptions constructively
• Experience partnering closely with cross-functional stakeholders to influence decisions
• Good judgment when tailoring analytical toolkit to the problem at hand
• Fluency in English is required due to the percentage of English-speaking customers and the nature of our platform, which is available to all Canadians

Desirable

• We’re re-instating a dedicated Risk team at Shakepay to build the next generation of our risk systems and decisioning capabilities
• The team’s mission is to enable sustainable business growth by protecting customers, Shakepay, and the broader financial ecosystem from abuse - while balancing fraud prevention, regulatory compliance, customer experience, and operational efficiency
• This is a small, newly formed team (starting with two engineers and a dedicated data partner) with significant ownership and ambiguity
• The team works closely across fraud, decision science, security, compliance, customer support, and product to build foundational risk systems, data infrastructure, and decision frameworks
• We’re looking for a Senior Data Scientist to help define how Shakepay measures, understands, and manages risk
• This role is analytics-first, with selective use of machine learning where it meaningfully improves understanding or decision quality
• Partner with Risk, Engineering, Security, Compliance, and Operations to define risk metrics and success criteria
• Analyze fraud, scam, and abuse patterns across crypto and fiat products
• Build and maintain dashboards tracking fraud loss, false positives, customer friction, and operational efficiency
• Improve data instrumentation and data quality for risk-related events and decisions
• Evaluate and iterate on risk rules and controls using rigorous analysis
• Apply statistical and ML techniques to surface signals, segment risk, and prioritize interventions
• Conduct deep-dive investigations into incidents, trends, and emerging threats
• Communicate insights clearly and persuasively to senior stakeholders
• Help establish data standards and best practices within the Risk team