Senior Data Scientist I - Meals

Accountabilities: • Lead data science for the Meals initiative, supporting the post-MVP scale-up of data science systems, measurement, and infrastructure.

• Design, build, and maintain metric-tracking frameworks to measure engagement, activation, reactivation, and broader product impact.

• Define and lead experimentation strategies, from hypothesis development and experiment design through analysis, interpretation, and recommendations.

• Apply A/B testing, causal inference, statistical modeling, and product analytics to guide product strategy and decision-making.

• Define meaningful KPIs and optimize product funnels to support product-market fit and sustainable growth.

• Partner closely with Product Managers, Engineering Leads, Data Engineers, and Designers to align data science with product strategy.

• Communicate complex technical findings and analytical insights clearly to senior business and engineering stakeholders.

• Improve logging, instrumentation, metric definitions, and measurement practices across complex data environments.

• Connect offline evaluation metrics with online experimentation and business outcomes where relevant.

• Contribute to a high-visibility 0→1 initiative, helping establish what success looks like as the product moves toward scale.

Requirements:

• 4+ years of professional experience in data science or a related quantitative field.

• Proven experience in consumer-facing product data science and close collaboration with Product, Engineering, and Data teams.

• Strong foundation in product and data analysis, A/B experimentation, causal inference, and statistical modeling.

• Demonstrated ability to define KPIs, analyze product funnels, and use data to support product-market fit.

• Excellent communication skills, with the ability to synthesize complex analytical and technical findings for senior stakeholders.

• Bachelor’s degree in Statistics, Computer Science, Mathematics, Economics, Engineering, or another quantitative discipline, or equivalent practical experience.

• Experience with causal inference techniques beyond standard A/B testing, such as holdout groups, difference-in-differences, or quasi-experimental methods, is preferred.

• Experience connecting offline evaluation metrics such as NDCG, precision/recall, or human evaluation with online experiments and business outcomes is preferred.

• Proven experience improving logging, instrumentation, and metric definitions in complex data environments is a plus.

• Experience launching new features in new markets or contributing to 0→1 initiatives is preferred.

• Strong analytical thinking, structured problem-solving, stakeholder management, and cross-functional collaboration skills.

• Ability to operate effectively in a high-visibility environment where experimentation and data-driven decision-making are central to product development.

• Remote eligibility is currently limited to Ontario, Alberta, British Columbia, and Nova Scotia.

Benefits:

• $161,000–$170,000 CAD annual base salary for eligible Canadian-based candidates.

• New-hire equity grant.

• Annual equity refresh grants.

• Market-competitive compensation and benefits based on permanent work location.

• Fully remote work within eligible Canadian provinces.

• Flexible approach to where work is performed, supported by opportunities for regular in-person connection and team events.

• Opportunity to work on a high-visibility 0→1 product initiative with significant data science ownership.

• Close collaboration with Product, Engineering, Design, and Data teams.

• Exposure to experimentation, causal inference, product analytics, and large-scale measurement systems.

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