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.