We're looking for experienced economists and machine learning engineers to join our fast-moving team. The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making.
For our team, we are looking for economics or machine learning engineers with experience in bringing machine learning models to life. The ideal candidate for this position has a background in both economics and machine learning and past experience in creating end-to-end machine learning solutions. There is tremendous opportunity in front of us, and joining now gives you a chance to grow your career and interests as we succeed.
ABOUT THE JOB
You will build end-to-end machine learning solutions to bring models from conception to production.
You will be dedicated to a small cross-discipline product team, with tremendous ownership and responsibility for managing things directly.
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 Instacart's 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.
3+ years of academic or industry experience in an economics role, preferable working on data-intense problems
A graduate degree in economics or equivalent 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
Strong engineering skills with expertise in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
Experience with training large-scale models and model deployment on cloud services (Docker, AWS/GCP/Azure).
An ability to identify and prioritize high-impact problems and deliver solutions that provide reasonable trade-offs between urgency and quality.
Willing and able to travel internationally based on job requirements
Expertise in causal inference with observational and experimental data
Self-motivation and a strong sense of ownership
B.Sc. (required), M.S./PhD (preferred) in Computer Science, Economics, Mathematics, Statistics or related field