Economist - Machine Learning Engineer
San Francisco, CA
Applications have closed
Instacart
Order same-day delivery or pickup from more than 300 retailers and grocers. Download the Instacart app or start shopping online now with Instacart to get groceries, alcohol, home essentials, and more delivered to you <b>in as fast as 1 hour</b>...OVERVIEW
We're looking for 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.
The ideal candidate will bring a combination of experience in both economics and machine learning. This might be a recent economics PhD graduate with relevant computationally intensive empirical research and some exposure to machine learning coursework and applications. Alternatively, we would be interested in a candidate with industry experience creating, deploying, and maintaining machine learning models at scale, especially if they have some background or experience in economics or an economics-adjacent field. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and causal inference.
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 help design and build end-to-end machine learning solutions.
- You will be dedicated to a small cross-discipline product team, 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 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.
ABOUT YOU
- Graduate-level research experience on data-intense problems or 2+ years of industry experience in machine learning or economics-focused roles.
- A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one.
- Expertise in causal inference with observational and experimental data.
- Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (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.
- Willing and able to travel internationally based on job requirements
- Self-motivation and a strong sense of ownership
- Nice to have: Experience with training large-scale models and model deployment on cloud services (Docker, AWS/GCP/Azure).
Tags: AWS Azure Causal inference Docker Econometrics Economics Engineering GCP Keras Machine Learning ML models Model deployment Pandas PhD Python R Research Scikit-learn SQL TensorFlow Testing XGBoost
Perks/benefits: Career development
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