Lead Data Scientist

<h3>Accountabilities</h3><li>Investigate revenue opportunities and underlying data, translating findings into opportunities that can be sized, prioritized, tested, and measured.</li><li>Design, build, deploy, and operate production ML systems, including batch inference, online services, and online learning models for personalization, experimentation, and automation.</li><li>Partner with Product, Mobile Engineering, Cloud Engineering, Data Engineering, and MLOps teams to integrate ML capabilities into customer-facing experiences.</li><li>Establish monitoring and measurement frameworks to evaluate model performance, product outcomes, and business impact.</li><li>Implement data, code, and model lineage practices that support secure, reproducible, and compliant ML lifecycles.</li><li>Collaborate with Data Engineering to improve pipelines and the broader data ecosystem supporting experimentation and machine learning.</li><li>Apply causal inference, experimentation, and advanced analytics to guide product and revenue decisions.</li><li>Mentor data scientists and contribute to best practices for advanced analytics, experimentation, and production ML development.</li><li>Use Claude Code and other AI tools throughout data discovery, modeling, coding, experiment evaluation, and workflow optimization.</li><li>Share effective AI workflows and help raise the technical and AI fluency of surrounding data science and engineering teams.</li><h2>Requirements</h2><li>6+ years of professional experience scoping, building, analyzing, and deploying ML-powered systems, including models successfully shipped to production.</li><li>Advanced degree in a quantitatively rigorous discipline involving sophisticated statistical analysis, or equivalent industry experience.</li><li>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.</li><li>Demonstrated technical training and professional experience applying modern causal inference and causal analysis techniques.</li><li>Strong experience working with existing datasets, designing instrumentation to generate new data, and building transformations for complex analyses and ML systems.</li><li>Hands-on experience designing, monitoring, and analyzing experiments in consumer technology environments.</li><li>Experience building ML systems or running experiments within B2C technology, ideally involving subscriptions, transactions, advertising, or other revenue-generating products.</li><li>Strong communication, stakeholder management, and project leadership skills, with the ability to influence cross-functional teams and explain complex analytical findings clearly.</li><li>A structured, hypothesis-driven approach to solving ambiguous problems, including situations where data is incomplete or unavailable.</li><li>Experience leveraging LLMs and generative AI for advanced data processing, analysis, development, or other data science workflows.</li><li>Experience with digital advertising, ad technology infrastructure, content ranking, or feed algorithms is an advantage.</li><li>Familiarity with production feature stores, ML model registries, subscription products, lifecycle marketing, user acquisition, revenue forecasting, or geospatial and mobile location data is preferred.</li><li>Demonstrated ability to critically review AI-generated code, analyses, and models and take full ownership of production outcomes.</li><li>Willingness to continuously explore emerging AI tools, run practical experiments with them, and translate useful discoveries into team practices.</li><h2>Benefits</h2><li>Competitive annual base salary for Canada of<strong>$171,500–$202,500 CAD</strong>, with final compensation determined by experience, skills, background, and location.</li><li>Equity compensation through Restricted Stock Units (RSUs) as part of the total compensation package.</li><li>Comprehensive benefits including medical, dental, vision, life, and disability coverage; supplemental medical and dental benefits are available for Canadian employees.</li><li>RRSP with a DPSP plan for Canadian employees.</li><li>Paid parental leave.</li><li>Mental Wellness Program and Employee Assistance Program (EAP).</li><li>Flexible paid time off, companywide holidays, and summer and winter shutdown periods.</li><li>Learning and development programs to support continued professional growth.</li><li>Equipment, tools, and reimbursement support for an effective remote working environment.</li><li>Remote-first work culture for employees working from Canada.</li><li>Complimentary premium membership and connected-device benefits.</li>