Description
At Instacart, we're transforming the grocery industry by delivering an essential service that customers rely on to get their groceries and household goods. As a Senior Machine Learning Engineer, Economist, you will build state-of-the-art systems that blend rigorous economic thought with sophisticated machine learning algorithms to tackle some of the company's most challenging problems.
Overview
As a machine learning engineer in the Economics team, you will have the opportunity to collaborate closely with partners across multiple functions to operate on a highly diverse set of problems, contributing both economic and engineering expertise in a fast-paced environment filled with exciting opportunities for technically-minded economists.
Responsibilities
- Design, develop, and deploy machine learning solutions to tackle the many economic challenges in our complex marketplace.
- Collaborate closely with product managers, data scientists, and other engineers to deeply understand business needs and create impactful solutions.
- Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.
- Be an active member of the Economics team, sharing learnings, best practices, and research across domains while refining and advancing our algorithms.
Requirements
- Graduate Degree (Masters or PhD) in Economics or a closely related field.
- A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one.
- Experience applying causal inference methodologies to both observational and experimental datasets.
- An understanding of machine learning algorithms and techniques.
- Strong programming skills (Python) and fluency in data manipulation (SQL, Pandas) and machine learning tools (e.g., scikit-learn, XGBoost).
- Excellent communication skills (both verbal and written).
- Self-motivation and a strong sense of ownership.
Preferred Qualifications
- A PhD in Economics or a closely related field with a focus on data-intense problems.
- Intern experience in related roles.
- Experience with large language models and generative AI, both on the algorithm side as well as a day-to-day tool.
- Experience with uplift modeling, contextual bandits, and/or heterogeneous treatment effect estimation.