Overview

As a machine learning engineer in the Economics team, 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. Working in a horizontal 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.

The Economics team at Instacart works on a range of interesting and challenging problems across our platform, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include matching and logistics, online advertising, uplift and long-term value modeling, and general causal inference. Check out this blog post to learn more.

About the Job

• 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.

About You

We are open to hiring either a Machine Learning Engineer II, Economist (fresh PhD graduate) or a Senior Machine Learning Engineer I, Economist (post-PhD industry experience).

Minimum Qualifications

• 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.

For Senior Machine Learning Engineer I, Economist hires, we also expect:

• 1-3 years of industry experience in a similar position.
• Experience putting machine learning models into production environments.
• Experience with cloud computing and related ML infrastructure.

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.

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