Senior Data Scientist I - Meals
About this role
Driving the Meals initiative involves leading data science efforts to scale systems and infrastructure following the initial MVP launch. Metric tracking and experimentation form the core of daily responsibilities, with a focus on boosting engagement, activations, and reactivations for a high-visibility product area. Close collaboration with Product, Engineering, and Design teams shapes the direction of this 0 to 1 initiative at a critical inflection point.
Ownership of the post-MVP scale-up requires designing metric tracking frameworks and guiding the experimentation strategy from hypothesis definition to final recommendation. Success in the position demands a strong foundation in consumer-facing product data science, statistical modeling, and A/B testing. Candidates who excel here possess a mix of technical rigor and clear communication skills, enabling them to translate complex findings for diverse stakeholders.
What you will do
- Lead data science operations for the Meals initiative, taking ownership of the post-MVP scale-up of data science systems and infrastructure.
- Design, build, and maintain comprehensive metric tracking frameworks to measure the impact of the initiative on user engagement, activation, and reactivation.
- Drive the full experimentation strategy from hypothesis definition through to rigorous analysis and actionable recommendations.
- Partner closely with Product Managers, Engineers, and Designers to align on product strategy and communicate data-driven insights.
- Contribute directly to a high-impact 0 to 1 initiative during a critical growth phase by helping define success metrics at scale.
What you need
- Bring four or more years of professional work experience in a data science or a closely related quantitative field.
- Hold a Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Economics, or Engineering, or possess equivalent practical experience.
- Demonstrate proven experience in consumer-facing product data science while partnering with Product Managers, Engineering Leads, and Data Engineers.
- Apply a strong foundation in product and data analysis, A/B experimentation, causal inference, and statistical modeling.
- Define key performance indicators and optimize funnels to support product market fit.
- Communicate clearly and synthesize complex technical findings for senior business and engineering stakeholders.
Nice to have
- Experience bridging offline evaluation metrics like NDCG, precision and recall, or human evaluation with online experiments and business outcomes.
- Background in causal inference beyond standard A/B tests, including holdouts, diff-in-diff, and quasi-experiments to measure long-term or cross-surface effects.
- Proven impact improving logging, instrumentation, and metric definitions in complex data environments.
- Experience launching new features in new markets or driving 0 to 1 initiatives.
Benefits
- Market-competitive compensation with a base pay range of $161,000 to $170,000 CAD
- New hire equity grant as well as annual refresh grants
- Flex First remote work policy allowing employees to work from home, an office, or other locations
Questions candidates ask
What is the remote work policy for this role?
Instacart operates under a Flex First remote work policy where employees have the flexibility to choose where they do their best work. Currently, hiring for this role is restricted to candidates residing in Ontario, Alberta, British Columbia, and Nova Scotia.
What is the salary range for the position?
The base pay range for a successful candidate in Canada is $161,000 to $170,000 CAD. Offers may vary based on factors such as candidate experience and permanent work location.
What additional financial compensation is provided beyond base salary?
The role is eligible for a new hire equity grant as well as annual refresh grants. Market-competitive compensation and benefits are provided in each work location.
What core project will this data scientist lead?
The person in this position will lead data science for the Meals initiative, which is one of the company's top strategic priorities. The work focuses on scaling data science systems following the MVP launch with an emphasis on metric tracking and experimentation.