OVERVIEW

We’re looking for economists and machine learning engineers to join our fast paced Economics team! We work on a range of exciting challenges, from aligning the incentives in our multi-sided marketplace, to analyzing the role of prices and product placement in our customers’ decision-making.

This is an opportunity to work in areas critical to our business, like pricing, online advertising, uplift and long term value modeling, and causal inference.

ABOUT THE JOB

On the Economics team we build machine learning solutions, and bring models from conception to production. You’ll be part of an outstanding internal community, with the opportunity to share findings, methodologies and research across domains. You will be dedicated to a cross-functional product team, with tremendous ownership and responsibility for directly leading projects. You’ll also:

• Develop high impact solutions to support Instacart’s ambitious growth plans.
• Work closely with engineers, product managers, other teams, and both internal and external partners. You’ll be responsible for a large part of the process, from problem understanding to recommending a solution and testing it in controlled experiments.
• Have the freedom to suggest and drive organization-wide initiatives!

ABOUT YOU

Minimum qualifications

A PhD in economics or the equivalent industry/academic experience. A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one. We’re looking for people with self-motivation and a strong sense of ownership, as well as:

• Strong engineering skills, with expertise in Python and proficiency in data manipulation (SQL, Spark, Pandas) and ML (scikit-learn, XGBoost, Keras/Tensorflow) tools
• An ability to identify and prioritize high-impact problems and deliver solutions that provide reasonable trade-offs between urgency and quality.
• Expertise in causal inference with observational and experimental data

Preferred qualifications

6+ years of experience in industry and/or academia, preferably working on data-intense problems. Experience training large-scale models and model deployment on cloud services (Docker, AWS/GCP/Azure) will be valuable. Willing and able to travel internationally based on job requirements.

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