
Enrichment Operations Analyst
- Toronto, ON
- $99,000-110,000 per year
- Permanent
- Full-time
- Scale attribute data generation using ML. Collaborate with ML on attribute ML models and human-in-the-loop methodologies. You are responsible for building ground truth datasets, advising ML on what input data should be used, and building LLM prompts. You will also develop sourcing strategies on the best way to generate data for new attributes to power customer experiences. This requires thinking from both a technical/data point of view while also understanding how data should be presented to a customer on the app.
- Evaluate model outputs (including criteria to decide on accuracy of outputs) to provide feedback to the ML team to improve models. This may involve reviewing and leading work from QA team members.
- Collaborate with Product, Engineering, Data Science, and ML to execute on projects that roll up to catalog OKRs (e.g., increase attribute coverage).
- Independently lead key projects and manage against catalog OKRs. This involves collaborating and aligning with a cross-functional team of technical and non-technical stakeholders to achieve the goals of a project within a defined timeframe.
- Manage relationships and data pipelines with 3rd party vendors and data providers that provide catalog data to Instacart. Use SQL to analyze data and present data-driven business recommendations.
- 1-3 years of working experience in roles that involved project management, project delivery, stakeholder management, strategy and operations, and/or data analysis/analytics.
- Bachelor's degree in business, commerce, economics, IT management, or related field.
- Experience leading cross-functional projects end-to-end, with strong communication and stakeholder management skills. Experience working closely with Product, Engineering, ML, and DS teams preferred. Proven track record of strong ownership and bias to action to drive key business results.
- Ability to blend business acumen with technical understanding to drive operational strategy and execution.
- Intermediate knowledge in Excel, Google Sheets, and SQL. Experience using analytical skills to pull, analyze, and make data-driven business decisions.
- Experience working with databases that contain large volumes of structured and unstructured data. Working knowledge of APIs and data integrations.
- Experience working at an e-commerce, retail, or technology company.
- Experience crafting LLM prompts.
- Our team prefers to get together in-office 1x a week.