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 Lead Data Scientist based in Canada.

• Investigate revenue opportunities and underlying data, translating findings into opportunities that can be sized, prioritized, tested, and measured.
• Design, build, deploy, and operate production ML systems, including batch inference, online services, and online learning models for personalization, experimentation, and automation.
• Partner with Product, Mobile Engineering, Cloud Engineering, Data Engineering, and MLOps teams to integrate ML capabilities into customer-facing experiences.
• Establish monitoring and measurement frameworks to evaluate model performance, product outcomes, and business impact.
• Implement data, code, and model lineage practices that support secure, reproducible, and compliant ML lifecycles.
• Collaborate with Data Engineering to improve pipelines and the broader data ecosystem supporting experimentation and machine learning.
• Apply causal inference, experimentation, and advanced analytics to guide product and revenue decisions.
• Mentor data scientists and contribute to best practices for advanced analytics, experimentation, and production ML development.
• Use Claude Code and other AI tools throughout data discovery, modeling, coding, experiment evaluation, and workflow optimization.
• Share effective AI workflows and help raise the technical and AI fluency of surrounding data science and engineering teams.

• 6+ years of professional experience scoping, building, analyzing, and deploying ML-powered systems, including models successfully shipped to production.
• Advanced degree in a quantitatively rigorous discipline involving sophisticated statistical analysis, or equivalent industry experience.
• Strong programming experience with Python, scikit-learn, PySpark, and tools for causal inference, alongside solid software engineering practices such as testing, modularization, and version control.
• Demonstrated technical training and professional experience applying modern causal inference and causal analysis techniques.
• Strong experience working with existing datasets, designing instrumentation to generate new data, and building transformations for complex analyses and ML systems.
• Hands-on experience designing, monitoring, and analyzing experiments in consumer technology environments.
• Experience building ML systems or running experiments within B2C technology, ideally involving subscriptions, transactions, advertising, or other revenue-generating products.
• Strong communication, stakeholder management, and project leadership skills, with the ability to influence cross-functional teams and explain complex analytical findings clearly.
• A structured, hypothesis-driven approach to solving ambiguous problems, including situations where data is incomplete or unavailable.
• Experience leveraging LLMs and generative AI for advanced data processing, analysis, development, or other data science workflows.
• Experience with digital advertising, ad technology infrastructure, content ranking, or feed algorithms is an advantage.
• Familiarity with production feature stores, ML model registries, subscription products, lifecycle marketing, user acquisition, revenue forecasting, or geospatial and mobile location data is preferred.
• Demonstrated ability to critically review AI-generated code, analyses, and models and take full ownership of production outcomes.
• Willingness to continuously explore emerging AI tools, run practical experiments with them, and translate useful discoveries into team practices.

• Competitive annual base salary for Canada of $171,500–$202,500 CAD, with final compensation determined by experience, skills, background, and location.
• Equity compensation through Restricted Stock Units (RSUs) as part of the total compensation package.
• Comprehensive benefits including medical, dental, vision, life, and disability coverage; supplemental medical and dental benefits are available for Canadian employees.
• RRSP with a DPSP plan for Canadian employees.
• Paid parental leave.
• Mental Wellness Program and Employee Assistance Program (EAP).
• Flexible paid time off, companywide holidays, and summer and winter shutdown periods.
• Learning and development programs to support continued professional growth.
• Equipment, tools, and reimbursement support for an effective remote working environment.
• Remote-first work culture for employees working from Canada.
• Complimentary premium membership and connected-device benefits.