Overview
We are looking for interns to join Instacart's Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in economics or related fields like marketing, finance, or operations research. Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications.
The Economics team at Instacart works on a range of interesting and challenging problems at the intersection of machine learning and economics, from aligning the incentives in our multi-sided marketplace to analyzing the impact of behavioral nudges on our customers' and shoppers' decisions. Some of the core areas of focus for our team include online advertising, uplift and long term value modeling, logistics, marketplace optimization (consumers, shoppers, retailers), inventory intelligence, and general causal inference. You can find more information in our blog post that introduces the team and the type of work we do.
About the Job
You will help design and build end-to-end machine learning solutions.
You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects.
You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains.
You will develop high impact solutions to support Instacarts ambitious growth plans.
You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments.
You will have the freedom to suggest and drive organization-wide initiatives.
About You
Minimum Qualifications
Current or recently graduated PhD student in economics or a related field with focus on data-intense problems.
A blend of economic theory, applied econometrics, and business acumen that let you jump into a fast-paced environment and contribute from day one.
Expertise in causal inference with observational and experimental data.
Expertise in Python or R and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
Self-motivation and a strong sense of ownership