Senior Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Canada. As a Senior Data Scientist, you will shape product strategy through rigorous analytics, experimentation, and data-informed decision-making. You’ll work as a senior individual contributor alongside Product, Engineering, Design, Finance, and Operations. The role combines product analytics, statistical experimentation, causal inference, and scalable analytics infrastructure. You’ll turn complex and ambiguous product questions into actionable insights that influence roadmap and business decisions. You’ll also help build experimentation frameworks and self-service analytics capabilities that enable teams to move faster with confidence. Working in a global, fast-paced environment, you’ll have meaningful ownership over how data drives product experiences, growth, and monetization. You’ll also mentor peers and contribute to establishing strong analytical practices across the organization. \n Accountabilities: - Analyze the full product funnel, including onboarding, KYC, funding, and trading, to identify growth opportunities and improve key product and business metrics. - Design and build experimentation tooling, frameworks, statistical standards, and guardrails that enable reliable A/B testing and causal-inference studies at scale. - Define, maintain, and improve key product performance metrics in partnership with analytics engineering, ensuring they are governed, scalable, and accessible through trusted dashboards. - Partner closely with Product, Engineering, Design, Finance, and Operations to integrate data and experimentation into the product development lifecycle. - Translate complex datasets and analytical findings into clear visualizations, narratives, recommendations, and business insights for stakeholders and senior leadership.

- Help transition analytics from ad-hoc requests to intuitive self-service environments, including contributions to text-to-analytics capabilities built on a semantic layer. - Mentor data scientists and analysts, establish analytical best practices, and contribute to a strong data-informed product culture. - Identify opportunities to apply automation and emerging analytical approaches to improve the speed, consistency, and accessibility of decision-making. Requirements: - Proven experience in product analytics and data science, with strong expertise in statistical analysis, experimentation, and data-driven product development. - Experience designing or building experimentation platforms, frameworks, or methodologies that support trustworthy A/B testing and causal-inference analysis. - Strong programming and analytical skills in Python and SQL, or comparable languages and technologies. - Advanced understanding of statistical methods, experimentation principles, causal inference, predictive modeling, and analytical problem-solving. - Experience translating complex analysis into clear recommendations and communicating effectively with both technical and non-technical stakeholders. - Strong cross-functional collaboration skills and the ability to influence product direction through evidence and clear reasoning. - Experience creating effective data visualizations and using analytical storytelling to communicate insights. - Demonstrated ability to take ownership of projects, operate independently, and deliver results in a fast-paced environment. - Strong critical and creative thinking, with the ability to turn ambiguous business and product questions into structured analytical approaches. - A Master's or PhD in a quantitative discipline such as mathematics, statistics, engineering, economics, or natural sciences. - Typically 6–10 years of experience developing and deploying predictive models and applying advanced data science techniques.